Dissertations / Theses: 'Public health Data processing'

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Chitondo, Pepukayi David Junior. "Data policies for big health data and personal health data." Thesis, Cape Peninsula University of Technology, 2016. http://hdl.handle.net/20.500.11838/2479.

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Thesis (MTech (Information Technology))--Cape Peninsula University of Technology, 2016. Health information policies are constantly becoming a key feature in directing information usage in healthcare. After the passing of the Health Information Technology for Economic and Clinical Health (HITECH) Act in 2009 and the Affordable Care Act (ACA) passed in 2010, in the United States, there has been an increase in health systems innovations. Coupling this health systems hype is the current buzz concept in Information Technology, „Big data‟. The prospects of big data are full of potential, even more so in the healthcare field where the accuracy of data is life critical. How big health data can be used to achieve improved health is now the goal of the current health informatics practitioner. Even more exciting is the amount of health data being generated by patients via personal handheld devices and other forms of technology that exclude the healthcare practitioner. This patient-generated data is also known as Personal Health Records, PHR. To achieve meaningful use of PHRs and healthcare data in general through big data, a couple of hurdles have to be overcome. First and foremost is the issue of privacy and confidentiality of the patients whose data is in concern. Secondly is the perceived trustworthiness of PHRs by healthcare practitioners. Other issues to take into context are data rights and ownership, data suppression, IP protection, data anonymisation and reidentification, information flow and regulations as well as consent biases. This study sought to understand the role of data policies in the process of data utilisation in the healthcare sector with added interest on PHRs utilisation as part of big health data.

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Indrakanti, Saratchandra. "Computational Methods for Vulnerability Analysis and Resource Allocation in Public Health Emergencies." Thesis, University of North Texas, 2015. https://digital.library.unt.edu/ark:/67531/metadc804902/.

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POD (Point of Dispensing)-based emergency response plans involving mass prophylaxis may seem feasible when considering the choice of dispensing points within a region, overall population density, and estimated traffic demands. However, the plan may fail to serve particular vulnerable sub-populations, resulting in access disparities during emergency response. Federal authorities emphasize on the need to identify sub-populations that cannot avail regular services during an emergency due to their special needs to ensure effective response. Vulnerable individuals require the targeted allocation of appropriate resources to serve their special needs. Devising schemes to address the needs of vulnerable sub-populations is essential for the effectiveness of response plans. This research focuses on data-driven computational methods to quantify and address vulnerabilities in response plans that require the allocation of targeted resources. Data-driven methods to identify and quantify vulnerabilities in response plans are developed as part of this research. Addressing vulnerabilities requires the targeted allocation of appropriate resources to PODs. The problem of resource allocation to PODs during public health emergencies is introduced and the variants of the resource allocation problem such as the spatial allocation, spatio-temporal allocation and optimal resource subset variants are formulated. Generating optimal resource allocation and scheduling solutions can be computationally hard problems. The application of metaheuristic techniques to find near-optimal solutions to the resource allocation problem in response plans is investigated. A vulnerability analysis and resource allocation framework that facilitates the demographic analysis of population data in the context of response plans, and the optimal allocation of resources with respect to the analysis are described.

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Asiimwe, Sarah. "Use of health information for operational and strategic decision-making by division level managers of Kampala City Council Health Department." Thesis, University of the Western Cape, 2002. http://etd.uwc.ac.za/index.php?module=etd&amp.

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O'Donnell, Melissa. "Towards prevention - a population health approach to child abuse and neglect : health indicators and the identification of antecedent causal pathways." University of Western Australia. School of Paediatrics and Child Health, 2009. http://theses.library.uwa.edu.au/adt-WU2010.0029.

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[Truncated abstract] The primary aims of this thesis were to investigate health indicators of child maltreatment, as well as pathways into the child protection system using routinely collected government databases, enabling a preventative health approach to child abuse and neglect. This thesis aims to improve understanding of the trends in child maltreatment and the factors, at the child and family level, which increase or reduce vulnerability to child maltreatment so more effective prevention policies and practices can be developed. This project uses longitudinal de-identified population data from the Western Australian Government Departments of Child Protection, Health and Disability Services. These data contained information on demographic, clinical, social and child protection outcomes of children and their families. Record linkage of administrative data was undertaken to: investigate health indicators of abuse and neglect using Hospital Morbidity data to enable the monitoring of population trends in abuse and neglect; compare proportion of cases obtained using health indicators with the Department of Child Protection data, and describe the physical, psychological and social characteristics of abused and/or neglected children and families. Statistical techniques utilised include logistic and Cox regression to investigate risk of adverse child outcomes, taking into account potential confounding and time to event. The main findings include: There has been an increase in assault and maltreatment related hospital admissions over the last 25 years. ... There has been a marked increase in the birth prevalence of Neonatal Withdrawal Syndrome (NWS) in Western Australia over the last 25 years, from 1 per 10,000 live births in 1980, to 31 per 10,000 live births in 2005. Specific maternal characteristics associated with having a child with NWS are identified and these children have an increased risk of child protection involvement. A population level analysis of child and parental factors determined the estimated increase in risk of substantiated child maltreatment for child intellectual disability, parental admissions for mental health, substance use, and assault, as well as greater socio-economic disadvantage. Conclusions This is the first body of research which has extensively used longitudinal, population level linked health and child protection data to investigate health indicators of child abuse and neglect and antecedent causal pathways. Monitoring injuries and conditions associated with child abuse and neglect in routinely collected data and using multiple sources of ascertainment are important initiatives in child maltreatment surveillance. Health indicators of child abuse and neglect are not subject to the same definitional and policy issues as child protection data and therefore provide a more valid comparison over time and between jurisdictions. The identification of factors which increase vulnerability for children and families to child maltreatment is essential in the implementation of prevention strategies including universal public health approaches as well as the identification of at-risk families for targeted intervention.

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Chartree, Jedsada. "Monitoring Dengue Outbreaks Using Online Data." Thesis, University of North Texas, 2014. https://digital.library.unt.edu/ark:/67531/metadc500167/.

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Internet technology has affected humans' lives in many disciplines. The search engine is one of the most important Internet tools in that it allows people to search for what they want. Search queries entered in a web search engine can be used to predict dengue incidence. This vector borne disease causes severe illness and kills a large number of people every year. This dissertation utilizes the capabilities of search queries related to dengue and climate to forecast the number of dengue cases. Several machine learning techniques are applied for data analysis, including Multiple Linear Regression, Artificial Neural Networks, and the Seasonal Autoregressive Integrated Moving Average. Predictive models produced from these machine learning methods are measured for their performance to find which technique generates the best model for dengue prediction. The results of experiments presented in this dissertation indicate that search query data related to dengue and climate can be used to forecast the number of dengue cases. The performance measurement of predictive models shows that Artificial Neural Networks outperform the others. These results will help public health officials in planning to deal with the outbreaks.

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Mchunu, Nokubalela Ntombiyethu. "Adequacy of healthcare information systems to support data quality in the public healthcare sector, in the Western Cape, South Africa." Thesis, Cape Peninsula University of Technology, 2012. http://hdl.handle.net/20.500.11838/1387.

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Thesis submitted in fulfilment of the requirements for the degree Master of Technology (MTech) in Information Technology In the Faculty of Informatics and Design, at the Cape Peninsula University of Technology (CPUT), 2013 Healthcare services are vital to all human beings, as our daily lives depend on them. In South Africa approximately eighty per cent of the population uses the public healthcare services. In the current healthcare systems data corruption exists which threatens data quality in the systems. The aim of this study was to understand the existing information handling processes and factors that affect the accuracy and integrity of healthcare data. A qualitative research methodology, under the interpretive paradigm was used for this investigation. Activity theory is used to formulate an analytical framework, the “healthcare information system data quality activity theory framework”. This was very helpful for understanding the healthcare information handling process as an activity system that consists of actors with individual goals. Though the goals are varied, they are joined together by the common objective. The logic of the framework is that a realisation of goals in the activity system depends on a number of factors. At the beginning, there must be a synchronous inter-linkage between the goals of the actors, the mediating factors such as adequate tools, user skills, enabling policies, and the systematic procedures that are diligently enforced. It is assumed that any situation which prevents this inter-linkage will have a negative impact on the realisation of the sought objective. The framework therefore, was very helpful in informing questions, the data collection and ultimately, the analysis processes. The public healthcare sector is the main source of data; other sources were literature, the Internet and books. The analysis of data was done using content analysis to find what themes emerge and the relationship (s) between them in what is being analysed. The findings reveal a lack of adherence to information handling procedures and processes which lead to corrupt data in the systems. In addition, most users have limited skills, which is a hindrance to them in performing their duties as expected by the healthcare sector. In fact, the healthcare sector is also challenged by systems which are constantly slow or down, due to limited network capacity and human errors. The presence of these challenges suggests non-adherence to data handling procedures, which explains the existing corrupt data in the healthcare systems. Therefore the recommendation is that the public healthcare administration must enhance their training programs. The training must be re-designed to cater for the needs of all users, regardless of their background. It needs to improve user skills and boast their confidence in using electronic systems. Obviously, any changes and improvements need to be sustainable, and the sector is unlikely to succeed without enforcement of new procedures. Therefore, adherence to data handling procedures must be strictly enforced, with policies thoroughly communicated to the users. That way, the sector will not only have systems and related policies, but also ensure their full exploitation for improved service delivery in the public healthcare sector in South Africa.

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Wilmot, Peter Nicholas. "Modelling cooling tower risk for Legionnaires' Disease using Bayesian Networks and Geographic Information Systems." Title page, contents and conclusion only, 1999. http://web4.library.adelaide.edu.au/theses/09SIS.M/09sismw744.pdf.

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Includes bibliographical references (leaves 115-120) Establishes a Bayesian Belief Network (BBN) to model uncertainty of aerosols released from cooling towers and Geographic Information Systems (GIS) to create a wind dispersal model and identify potential cooling towers as the source of infection. Demonstrates the use of GIS and BBN in environmental epidemiology and the power of spatial information in the area of health.

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Lin, Dong. "Novel FDBC with creative technology for integrating advantages of distributed and centralized systems." Thesis, University of Macau, 2011. http://umaclib3.umac.mo/record=b2492977.

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Vuorio, R. (Riikka). "Use of public sector’s open spatial data in commercial applications." Master's thesis, University of Oulu, 2014. http://urn.fi/URN:NBN:fi:oulu-201311201883.

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The objective of this study was to analyse how young Finnish information technology (IT) companies utilize the public sector’s open spatial data. The aim was to find out to what extent companies use public sector’s open spatial data in products and how companies are using it. In addition, defects related to data and its use and companies’ awareness of public sector open data were canvassed. Defects and unawareness might prevent or retard the utilization of public sector’s data. Public sector is collecting vast amount of data from various areas when performing public tasks. The major part of the data is spatial, meaning the data has a location aspect. Public sector is opening the data for everybody to use freely and companies could use this open spatial data for commercial purposes. High expectations have been set for the data opening: along with it, innovations and business — new companies and digital products — will be created. The European Union has promoted greatly the public sector data opening with its legislative actions. First with the PSI directive (directive on re-use of public sector data) and later with the INSPIRE directive (directive on establishing and Infrastructure for Spatial Information in the European Community). The both directives are aiming to facilitate the re-use and dissemination of public sector data, whereas the INSPIRE directive has focused on the use of interoperable spatial data by creating the spatial data infrastructure. Even if the developments are still on going, these undertakings have already created possibilities for companies to use public sector data. This applies especially to the spatial data. This study was quantitative by nature and the empirical data for the study was collected through online survey, which was targeted to randomly selected Finnish IT companies established during the years 2009–2012. Data was analyzed by descriptive statistics. The results can be generalized to the whole target population in Finland. The results of this study shows that the number of companies utilizing public sector’s open spatial data is small and the public sector’s open spatial data has not yet enabled establishing of new companies. However, companies have developed few new products with the contribution of public sector’s open spatial data and the value of the data for the products is not minor. The thesis concludes that there is a need for greater investment in promoting the public sector’s open data amongst companies: the awareness of public sector’s open spatial data could be increased. In addition, coverage of datasets and interface services could be improved. Perhaps by eliminating these defects, the number of utilizers of public sector’s open spatial data would increase. Now there is a quiet sign of awakening of the business to utilize public sector’s data.

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Ponsimaa, P. (Petteri). "Discovering value for health with grocery shopping data." Master's thesis, University of Oulu, 2016. http://urn.fi/URN:NBN:fi:oulu-201605221849.

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Food retailers are taking more active role in the customer value creation process and shifting their attention from the sale of goods to support customer’s value-creation to discover more innovative service-based business models. From customer data consumers may develop more responsible consumption behaviour, make more economical choices, and raise awareness on food healthiness. This exploratory study sets out to answer the question what value if any does the use of grocery shopping data bring to the customers. Using design science research, the thesis makes use of grocery purchase data available to S-Group customers and presents ways of applying the data while making it meaningful for them. The aim was to construct visualization application prototypes for seeking value and benefits of purchase data experienced by the customers. To evaluate the application design, a study group of eight customers were invited to provide purchase data and feedback on the data visualizations. The focus was on building designs of the grocery consumption patterns based on customer interviews and then evaluating the impact on the study group via interviews and usage data. The visualization prototypes allowed the participants to discover something new of their shopping and food consumption behaviour, not known to them before the study and not visible from the mere purchase data. Interviews suggested that the visualizations of health data encourage reflection of consuming habits, and thus may be used as a tool for increasing awareness of one’s shopping behaviour. A number of limitations in the data utilization were met hindering inference-making and reflecting on the data. Lastly, the prototypes led the participants to envision new digital health services, some of which might have commercial value.

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Vossough, Ehsan. "Processing of continuous queries over infinite data streams." Access electronically, 2004. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20050112.154300/index.html.

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Hu, Jun. "Privacy-Preserving Data Integration in Public Health Surveillance." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/19994.

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With widespread use of the Internet, data is often shared between organizations in B2B health care networks. Integrating data across all sources in a health care network would be useful to public health surveillance and provide a complete view of how the overall network is performing. Because of the lack of standardization for a common data model across organizations, matching identities between different locations in order to link and aggregate records is difficult. Moreover, privacy legislation controls the use of personal information, and health care data is very sensitive in nature so the protection of data privacy and prevention of personal health information leaks is more important than ever. Throughout the process of integrating data sets from different organizations, consent (explicitly or implicitly) and/or permission to use must be in place, data sets must be de-identified, and identity must be protected. Furthermore, one must ensure that combining data sets from different data sources into a single consolidated data set does not create data that may be potentially re-identified even when only summary data records are created. In this thesis, we propose new privacy preserving data integration protocols for public health surveillance, identify a set of privacy preserving data integration patterns, and propose a supporting framework that combines a methodology and architecture with which to implement these protocols in practice. Our work is validated with two real world case studies that were developed in partnership with two different public health surveillance organizations.

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Das, Debalina. "Waterborne Diseases: Linking Public Health And Watershed Data." Amherst, Mass. : University of Massachusetts Amherst, 2009. http://scholarworks.umass.edu/theses/235/.

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Potok, Nancy Fagenson Newcomer Kathryn E. "Creating useful integrated data sets to inform public policy /." Click here for online access, 2009.

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Thesis (Ph. D.)--George Washington University, 2009. "A dissertation submitted to the faculty of the Columbian College of Arts and Sciences of the George Washington University in partial fulfillment of the requirements for the degree of Doctor of Philosophy." "August 31, 2009." "Dissertation directed by Kathryn Newcomber, Professor of Public Policy and Public Administration." Includes bibliographical references (p. 185-191).

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Adu-Prah, Samuel. "GEOGRAPHIC DATA MINING AND GEOVISUALIZATION FOR UNDERSTANDING ENVIRONMENTAL AND PUBLIC HEALTH DATA." OpenSIUC, 2013. https://opensiuc.lib.siu.edu/dissertations/657.

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Within the theoretical framework of this study it is recognized that a very large amount of real-world facts and geospatial data are collected and stored. Decision makers cannot consider all the available disparate raw facts and data. Problem-specific variables, including complex geographic identifiers have to be selected from this data and be validated. The problems associated with environmental- and public-health data are that (1) geospatial components of the data are not considered in analysis and decision making process, (2) meaningful geospatial patterns and clusters are often overlooked, and (3) public health practitioners find it difficult to comprehend geospatial data. Inspired by the advent of geographic data mining and geovisualization in public and environmental health, the goal of this study is to unveil the spatiotemporal dynamics in the prevalence of overweight and obesity in United States youths at regional and local levels over a twelve-year study period. Specific objectives of this dissertation are to (1) apply regionalization algorithms effective for the identification of meaningful clusters that are in spatial uniformity to youth overweight and obesity, and (2) use Geographic Information System (GIS), spatial analysis techniques, and statistical methods to explore the data sets for health outcomes, and (3) explore geovisualization techniques to transform discovered patterns in the data sets for recognition, flexible interaction and improve interpretation. To achieve the goal and the specific objectives of this dissertation, we used data sets from the National Longitudinal Survey of Youth 1997 (NLSY'97) early release (1997-2004), NLSY'97 current release (2005 - 2008), census 2000 data and yearly population estimates from 2001 to 2008, and synthetic data sets. The NLSY97 Cohort database range varied from 6,923 to 8,565 individuals during the period. At the beginning of the cohort study the age of individuals participating in this study was between 12 and 17 years, and in 2008, they were between 24 and 28 years. For the data mining tool, we applied the Regionalization with Dynamically Constrained Agglomerative clustering and Partitioning (REDCAP) algorithms to identify hierarchical regions based on measures of weight metrics of the U.S. youths. The applied algorithms are the single linkage clustering (SLK), average linkage clustering (ALK), complete linkage clustering (CLK), and the Ward's method. Moreover, we used GIS, spatial analysis techniques, and statistical methods to analyze the spatial varying association of overweight and obesity prevalence in the youth and to geographically visualize the results. The methods used included the ordinary least square (OLS) model, the spatial generalized linear mixed model (GLMM), Kulldorff's Scan space-time analysis, and the spatial interpolation techniques (inverse distance weighting). The three main findings for this study are: first, among the four algorithms ALK, Ward and CLK identified regions effectively than SLK which performed very poorly. The ALK provided more promising regions than the rest of the algorithms by producing spatial uniformity effectively related to the weight variable (body mass index). The regionalization algorithm-ALK provided new insights about overweight and obesity, by detecting new spatial clusters with over 30% prevalence. New meaningful clusters were detected in 15 counties, including Yazoo, Holmes, Lincoln, and Attala, in Mississippi; Wise, Delta, Hunt, Liberty, and Hardin in Texas; St Charles, St James, and Calcasieu in Louisiana; Choctaw, Sumter, and Tuscaloosa in Alabama. Demographically, these counties have race/ethnic composition of about 75% White, 11.6% Black and 13.4% others. Second, results from this study indicated that there is an upward trend in the prevalence of overweight and obesity in United States youths both in males and in females. Male youth obesity increased from 10.3% (95% CI=9.0, 11.0) in 1999 to 27.0% (95% CI=26.0, 28.0) in 2008. Likewise, female obesity increased from 9.6% (95% CI=8.0, 11.0) in 1999 to 28.9% (95% CI=27.0, 30.0) during the same period. Youth obesity prevalence was higher among females than among males. Aging is a substantial factor that has statistically highly significant association (p < 0.001) with prevalence of overweight and obesity. Third, significant cluster years for high rates were detected in 2003-2008 (relative risk 1.92, 3.4 annual prevalence cases per 100000, p < 0.0001) and that of low rates in 1997-2002 (relative risk 0.39, annual prevalence cases per 100000, p < 0.0001). Three meaningful spatiotemporal clusters of obesity (p < 0.0001) were detected in counties located within the South, Lower North Eastern, and North Central regions. Counties identified as consistently experiencing high prevalence of obesity and with the potential of becoming an obesogenic environment in the future are Copiah, Holmes, and Hinds in Mississippi; Harris and Chamber, Texas; Oklahoma and McCain, Oklahoma; Jefferson, Louisiana; and Chicot and Jefferson, Arkansas. Surprisingly, there were mixed trends in youth obesity prevalence patterns in rural and urban areas. Finally, from a public health perspective, this research have shown that in-depth knowledge of whether and in what respect certain areas have worse health outcomes can be helpful in designing effective community interventions to promote healthy living. Furthermore, specific information obtained from this dissertation can help guide geographically-targeted programs, policies, and preventive initiatives for overweight and obesity prevalence in the United States.

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Ling, Meng-Chun. "Senior health care system." CSUSB ScholarWorks, 2005. https://scholarworks.lib.csusb.edu/etd-project/2785.

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Senior Health Care System (SHCS) is created for users to enter participants' conditions and store information in a central database. When users are ready for quarterly assessments the system generates a simple summary that can be reviewed, modified, and saved as part of the summary assessments, which are required by Federal and California law.

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Dameh, Mustafa, and n/a. "Insights into gene interactions using computational methods for literature and sequence resources." University of Otago. Department of Anatomy & Structural Biology, 2008. http://adt.otago.ac.nz./public/adt-NZDU20090109.095349.

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At the beginning of this century many sequencing projects were finalised. As a result, overwhelming amount of literature and sequence data have been available to biologist via online bioinformatics databases. This biological data lead to better understanding of many organisms and have helped identify genes. However, there is still much to learn about the functions and interactions of genes. This thesis is concerned with predicting gene interactions using two main online resources: biomedical literature and sequence data. The biomedical literature is used to explore and refine a text mining method, known as the "co-occurrence method", which is used to predict gene interactions. The sequence data are used in an analysis to predict an upper bound of the number of genes involved in gene interactions. The co-occurrence method of text mining was extensively explored in this thesis. The effects of certain computational parameters on influencing the relevancy of documents in which two genes co-occur were critically examined. The results showed that indeed some computational parameters do have an impact on the outcome of the co-occurrence method, and if taken into consideration, can lead to better identification of documents that describe gene interactions. To explore the co-occurrence method of text mining, a prototype system was developed, and as a result, it contains unique functions that are not present in currently available text mining systems. Sequence data were used to predict the upper bound of the number of genes involved in gene interactions within a tissue. A novel approach was undertaken that used an analysis of SAGE and EST sequence libraries using ecological estimation methods. The approach proves that the species accumulation theory used in ecology can be applied to tag libraries (SAGE or EST) to predict an upper bound to the number of mRNA transcript species in a tissue. The novel computational analysis provided in this study can be used to extend the body of knowledge and insights relating to gene interactions and, hence, provide better understanding of genes and their functions.

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Jovic, Katarina. "Analysis of Customer Personal Data Processing in a Swedish Public Transport Organization." Thesis, Karlstads universitet, Handelshögskolan (from 2013), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-78037.

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Purpose: The purpose of this research is to analyze the current routine for processing customers’ personal data in a Swedish public transport organization and advise on improvements that might be made to better comply with GDPR. Methodology: A qualitative study of personal data (as defined in the GDPR) based on five telephone interviews. The interviews were held in Swedish, then transcribed and finally translated to English for analysis. Literature perspectives: A research (neutral) perspective of the implementation regarding the General Data Protection Regulation (GDPR) within an organization. It is reported that GDPR tend to increase the tension in an organization. Some organizations expect GDPR will increase the annual budget and believe the business strategy will be changed. Findings: The organization is interested to clearly implement the regulation to their best interest they can. The organization see the centralization of customers’ data as a positive outcome and want to continue with IT-support for the GDPR process to get automated. The organization expresses they want to create a good relationship with their customers and be clear with the purpose of data collection. Conclusions: The research suggests that the organization should invest in IT support, help guiding the employees to understand the purpose of GDPR and produce staff guidelines. The staff guidelines should cover most of the issues that may occur during daily routines. However, if any anomalies occur regarding GDPR, the data processor should act as a guide to the employee. Syfte: Syftet med kandidatuppsatsen är att analysera den nuvarande processen för bearbetning av kunders personuppgifter i en svensk kollektivtrafikorganisation samt ge förbättringsråd angående saker som kan förbättras för att bättre följa GDPR. Metod: En kvalitativ studie som handlar om personuppgifter (enligt definitionen i GDPR); baserat på fem telefonintervjuer. Intervjuerna hölls på svenska, transkriberades och översattes sedan till engelska för en analys. Teoretiska perspektiv: Ett forsknings- (objektivt) perspektiv på implementeringen av den allmänna dataskyddsförordningen (GDPR) inom en organisation. Det rapporteras att GDPR tenderar att öka stressen i en organisation. Vissa organisationer förväntar sig att GDPR kommer öka den årliga utgiften för databehandling samt tror att deras affärsstrategi kommer förändras. Resultat: Region Värmland Kollektivtrafik är intresserade av att genomföra GDPR förordningen i högsta grad. Organisationen ser centraliseringen av kundens personliga data som ett positivt resultat och vill fortsätta med IT-stöd för GDPR- processen för att den ska kunna bli automatiserad. Organisationen uttrycker att de vill skapa en bra relation med sina kunder och vara tydliga med syftet av datainsamlingen. Slutsatser: Studien antyder att organisationen bör investera i IT-stöd, hjälpa anställda att förstå syftet med GDPR samt ta fram personalriktlinjer. Personalriktlinjerna bör täcka de flesta problem som kan uppstå i de dagliga rutinerna. Om det däremot uppstår några avvikelser gällande GDPR, bör personbiträde fungera som en hjälpande hand för de anställda.

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Danna, Nigatu Mitiku, and Esayas Getachew Mekonnen. "Data Processing Algorithms in Wireless Sensor Networks får Structural Health Monitoring." Thesis, KTH, Bro- och stålbyggnad, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-72241.

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The gradual deterioration and failure of old buildings, bridges and other civil engineering structures invoked the need for Structural Health Monitoring (SHM) systems to develop a means to monitor the health of structures. Dozens of sensing, processing and monitoring mechanisms have been implemented and widely deployed with wired sensors. Wireless sensor networks (WSNs), on the other hand, are networks of large numbers of low cost wireless sensor nodes that communicate through a wireless media. The complexity nature and high cost demand of the highly used wired traditional SHM systems have posed the need for replacement with WSNs. However, the major fact that wireless sensor nodes have memory and power supply limitations has been an issue and many efficient options have been proposed to solve this problem and preserve the long life of the network. This is the reason why data processing algorithms in WSNs focus mainly on the accomplishment of efficient utilization of these scarce resources. In this thesis, we design a low-power and memory efficient data processing algorithm using in-place radix-2 integer Fast Fourier Transform (FFT). This algorithm requires inputs with integer values; hence, increases the memory efficiency by more than 40% and highly saves processor power consumption over the traditional floating-point implementation. A standard-deviation-based peak picking algorithm is next applied to measure the natural frequency of the structure. The algorithms together with Contiki, a lightweight open source operating system for networked embedded systems, are loaded on Z1 Zolertia sensor node. Analogue Device’s ADXL345 digital accelerometer on board is used to collect vibration data. The bridge model used to test the target algorithm is a simply supported beam in the lab.

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Harley, Joel B. "Data-Driven, Sparsity-Based Matched Field Processing for Structural Health Monitoring." Research Showcase @ CMU, 2014. http://repository.cmu.edu/dissertations/392.

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This dissertation develops a robust, data-driven localization methodology based on the integration of matched field processing with compressed sensing ℓ1 recovery techniques and scale transform signal processing. The localization methodology is applied to an ultrasonic guided wave structural health monitoring system for detecting, locating, and imaging damage in civil infrastructures. In these systems, the channels are characterized by complex, multi-modal, and frequency dispersive wave propagation, which severely distort propagating signals. Acquiring the characteristics of these propagation mediums from data represents a difficult inverse problem for which, in general, no readily available solution exists. In this dissertation, we build data-driven models of these complex mediums by integrating experimental guided wave measurements with theoretical wave propagation models and ℓ1 sparse recovery methods from compressed sensing. The data-driven models are combined with matched field processing, a localization framework extensively studied for underwater acoustics, to localize targets in complex, guided wave environments. The data-driven matched field processing methodology is then refined, through the use of the scale transform, to achieve robustness to environmental variations that distort guided waves. Data-driven matched field processing is experimentally applied to an ultrasound structural health monitoring system to detect and locate damage in aluminum plate structures.

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Yu, Donggang, and dyu@venus it swin edu au. "Processing and recognition of document and GIS images." Swinburne University of Technology, 2005. http://adt.lib.swin.edu.au./public/adt-VSWT20050812.095914.

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In intelligent document processing system and geographical information systems (GIS), the image processing and recognition play an important role. This thesis deals with various problems in processing images in documents and GIS: image smoothing, filling, linearization and extraction of contour features, extraction of structural points, separation and recognition of spurious segments in handwritten digits, reconstruction and recognition of broken digits, and separation and recognition of colour document and GIS images. These approaches are also called Optical Character Recognition (OCR). A new smoothing technique is developed to smooth follow contours of image. With the new smoothing algorithms, spurious pixels (points) of contours are removed based on smooth patterns, and smooth followed contours are found. Also, skeletons of image can be smoothed between neighboring �end� and �junction� points. Smooth following makes linearization of smoothed contours possible based on Freeman codes. A new filling algorithm of contours, project filling, is described based on two kinds of structural patterns. By this method, any complicated contours of images can be filled correctly. Different from other linearization methods, linearization and feature extraction of smoothed contours are based on difference chain codes. Curvature and bend angles of linearized are found. The convexity and concavity of linearized are described. In this way, a series of description features of contours is formed. Structural points are new and useful features to describe morphological structures between neighboring linearized lines. Extraction of structural points is based on structural patterns which are determined by element chain codes. Also, extension Freeman codes are used in this thesis. Structural points make description and recognition of contours possible. In order to recognize handwritten digits in document processing systems, separation of spurious segments, reconstruction of broken digits and recognition of handwritten digits are investigated. Experiments with large number of testing data set show satisfactory results for these algorithms. Separation and recognition of colour document and GIS images are discussed. Object images of document and GIS images are extracted based on the description of shape structures, prior knowledge and color information, which are associated with each other. Color images can be described by a limited number of colors in color document and GIS images. Therefore, separation of color image is done by color reduction method, and recognition of object images is based on structure patterns, prior knowledge and colour information. It can be seen that specific information should be considered in many practical problems to achieve better processing results.

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Korziuk, Kamil, and Tomasz Podbielski. "Engineering Requirements for platform, integrating health data." Thesis, Blekinge Tekniska Högskola, Institutionen för tillämpad signalbehandling, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-16089.

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In the world that we already live people are more and more on the run and population ageing significantly raise, new technologies are trying to bring best they can to meet humans’ expectations. Survey’s results, that was done during technology conference with elderly on Blekinge Institute of Technology showed, that no one of them has any kind of help in their home but they would need it. This Master thesis present human health state monitoring to focus on fall detection. Health care systems will not completely stop cases when humans are falling down, but further studying causes can prevent them.In this thesis, integration of sensors for vital parameters measurements, human position and measured data evaluation are presented. This thesis is based on specific technologies compatible with Arduino Uno and Arduino Mega microcontrollers, measure sensors and data exchange between data base, MATLAB/Simulink and web page. Sensors integrated in one common system bring possibility to examine the patient health state and call aid assistance in case of health decline or serious injury risk.System efficiency was based on many series of measurement. First phase a comparison between different filter was carried out to choose one with best performance. Kalman filtering and trim parameter for accelerometer was used to gain satisfying results and the final human fall detection algorithm. Acquired measurement and data evaluation showed that Kalmar filtering allow to reach high performance and give the most reliable results. In the second phase sensor placement was tested. Collected data showed that human fall detection is correctly recognized by system with high accuracy. Designed system as a result allow to measure human health and vital state like: temperature, heartbeat, position and activity. Additionally, system gives online overview possibility with actual health state, historical data and IP camera preview when alarm was raised after bad health condition.

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Kelman, Christopher William, and christopher kelman@cmis csiro au. "Monitoring Health Care Using National Administrative Data Collections." The Australian National University. National Centre for Epidemiology and Population Health, 2001. http://thesis.anu.edu.au./public/adt-ANU20020620.151547.

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With the inevitable adoption of information technology into all areas of human pursuit, the potential benefits for health care should not be overlooked. In Australia, details of most health care encounters are currently recorded for administrative purposes. This results in an impressive electronic data-bank that could provide a national resource for health service evaluation. ¶ Evaluation of health services has become increasingly important to provide indicators of the benefits, risks and cost-effectiveness of treatments. However, if administrative data are to be used for this purpose, several questions must first be addressed: Are the current data collections accessible? What outcome measures can be derived from these data? Can privacy issues be managed? Could the quality of the data be improved? Is the existing infrastructure adequate to supply data for evaluation purposes? Could the existing system provide a basis for the development of an integrated health information system? ¶ The aims of the project were: · To examine the potential for using administrative data to generate outcome measures and surveillance indicators. · To investigate the logistics of gaining access to these data for the purpose of research. This to be achieved within the current ethical, political and financial framework. · To compare the Australian health-service data system with the current international state-of-the-art. · To develop suggestions for expansion of the present system as part of an integrated health record and information system. This system to manage patient records and provide data for quality management, treatment surveillance and cost-effectiveness evaluation as a routine activity. ¶ The thesis is presented in two parts. In the first part, a historical cohort study is described that involved patients with implantable medical devices. The potential to evaluate outcomes was investigated using all national health-service information currently available in electronic form. Record linkage techniques were used to combine and augment the existing data collections. Australias national health databases are to varying degrees, amenable to such linkage and cover doctor visits, pharmaceuticals, hospital admissions and deaths. The study focused on medical devices as an illustrative case but the results are applicable to the routine assessment of all medical and surgical interventions. ¶ For the Australian Medical Devices study, the records of 5,316 patients who had medical device implants in 1993-94 were selected from the archives of a major private health insurer. Five groups of medical implants were studied: heart valves, pacemakers, hips, vascular grafts and intra-optic lenses. Outcomes for these patients, including death, re-operation and health service utilisation, were compared and analysed. ¶ A comparison study was performed using data from the Manitoba Health database in Winnipeg, Canada. Manitoba provides a very similar demographic group to that found in Australia and is an example of a prototype integrated-health-information system. One of the principal advantages for research is that personally identified data about medical and hospital services are collected for all patients. Selection bias is eliminated because individual consent is not required for this type of research and all selected patients could be included in the study. ¶ The two studies revealed many barriers to the use of administrative data for health outcomes research. Service event data for the Australian cohort could be collected but only after long delays and hospital morbidity data were not available for the entire cohort. In contrast to the situation in Australia, the Manitoba data were both accessible and complete, but were lacking in detail in some areas. ¶ Analysis of the collected data demonstrated that without the addition of clinical data only general indications of trends could be deduced. However, with minimal supplementary clinical data, it was possible to examine differences in performance between brands of medical devices thus indicating one of the uses for this type of data collection. ¶ In the second part of the thesis, conclusions are presented about the potential uses and limitations of the existing system and its use as a basis for the development of a national Integrated Health Record and Information System (IHRIS). The need for the establishment of a systemic quality management system for health care is discussed. ¶ The study shows that linked administrative data can provide information about health outcomes which is not readily available from other sources. If expanded and integrated, the system that is currently used to collect and manage administrative data, could provide the basis for a national health information system. This system would provide many benefits for health care. Benefits would include the monitoring, surveillance and cost-effectiveness analysis of new and existing treatments involving medical devices, drugs and surgical procedures. An integrated health information system could thus provide for both clinical and administrative needs, while in addition providing data for research. ¶ Unfortunately, in Australia, the use of administrative data for this purpose is not currently feasible. The principal barrier is the existence of a culture within the Australian health care system which is not supportive of research and is deficient in quality and safety measures. ¶ Recent initiatives by both the Commonwealth and state governments have supported the introduction of measures to improve quality and safety in health care. It is argued here that an Integrated Health Record and Information System (IHRIS) would provide an essential component of any such scheme. The results of this study have important policy implications for health care management in both the administrative and clinical domains.

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Maas, Luis C. (Luis Carlos). "Processing strategies for functional magnetic resonance imaging data sets." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/85262.

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Thesis (Ph.D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 1999. Includes bibliographical references (leaves 108-118). by Luis Carlos Maas, III. Ph.D.

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Arshad-Ayaz, Adeela. "Education and technology : a critical study of introduction of computers in Pakistani public schools." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102785.

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The importance of technology in education cannot be underestimated. There are compelling reasons for developing nations like Pakistan to introduce technology in their educational systems. Nevertheless the approach and methods used in introducing technology in schools are premised on an economic ideology and based on a techno-centric curriculum that leads to new forms of dependency by keeping individuals from controlling the decisions that significantly shape their lives. Introduction of technology does not automatically guarantee enhanced learning or effective teaching. Technology in education should be used as a tool to increase communication, create awareness, break down existing hierarchies, develop new styles of creating knowledge, and make schooling and education more inclusive. Mere technical use of computers in education does nothing to empower students. The techno-centric introduction of technology in Pakistani public schools is likely to produce inequality. A number of practices in Pakistan's educational and social structure will have to change for the potential of technology to be fully achieved. A shift is needed from 'learning about the computers' to 'using computers in learning', from 'acquisition of limited skills' to 'construction of knowledge', from 'teacher-dependency' to 'independent inquiry' and from 'teacher-centered' to 'student-centered' teaching methods. However, such a change can only take place within a critical framework of education. The critical model based on integrated curriculum treats the computer not as an isolated subject but as a tool that helps learners enhance their critical thinking skills and seek various alternatives to solve problems. Thus, it is important for educational policy-makers to realize that any effort at introducing technology in the educational realm requires theoretical discussion and a societal dialogue to arrive at a framework for technology's place in socio-educational contexts. Pakistan needs to develop and introduce educational technology to seek solutions for its unique economic, social, cultural and human and social development requirements based on its present level of development and evolution.

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Saunders, Patrick Joseph. "Investigating the public health impact of contaminated land using routinely available health data." Thesis, University of Birmingham, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.410601.

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Iwaya, Leonardo H. "Secure and Privacy-aware Data Collection and Processing in Mobile Health Systems." Licentiate thesis, Karlstads universitet, Institutionen för matematik och datavetenskap (from 2013), 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kau:diva-46982.

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Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance.

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Jeon, Seonghye. "Bayesian data mining techniques in public health and biomedical applications." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43712.

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The emerging research issues in evidence-based healthcare decision-making and explosion of comparative effectiveness research (CER) are evident proof of the effort to thoroughly incorporate the rich data currently available within the system. The flexibility of Bayesian data mining techniques lends its strength to handle the challenging issues in the biomedical and health care domains. My research focuses primarily on Bayesian data mining techniques for non-traditional data in this domain, which includes, 1. Missing data: Matched-pair studies with fixed marginal totals with application to meta-analysis of dental sealants effectiveness. 2. Data with unusual distribution: Modeling spatial repeated measures with excess zeros and no covariates to estimate U.S. county level natural fluoride concentration. 3. Highly irregular data: Assess overall image regularity in complex wavelet domain to classify mammography image. The goal of my research is to strengthen the link from data to decisions. By using Bayesian data mining techniques including signal and image processing (wavelet analysis), hierarchical Bayesian modeling, clinical trials meta-analyses and spatial statistics, this thesis resolves challenging issues of how to incorporate data to improve the systems of health care and bio fields and ultimately benefit public health.

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Zhang, Yan. "Improving the efficiency of graph-based data mining with application to public health data." Online access for everyone, 2007. http://www.dissertations.wsu.edu/Thesis/Fall2007/y_zhang_112907.pdf.

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Sharad, Chakravarthy Namindi. "Public Commons for Geospatial Data: A Conceptual Model." Fogler Library, University of Maine, 2003. http://www.library.umaine.edu/theses/pdf/SharadCN2003.pdf.

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Pigeon-Reesor, Helen. "A comparison of irritable bowel syndrome and Crohn's disease: Mechanisms underlying symptom processing and sickness impact." Thesis, University of Ottawa (Canada), 1992. http://hdl.handle.net/10393/10846.

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Previous research suggests an association between psychological dysfunction and Irritable Bowel Syndrome (IBS). We sought to confirm this relationship and examine the mechanisms by which psychosocial factors may amplify or maintain IBS complaints, and influence disability. One hundred and thirteen female participants, (45 IBS; 34 Crohn's; 34 healthy controls) were evaluated by psychological assessment which measured: symptom reporting, anxiety, depression, and impact of physical symptoms on daily activities. The assessment also evaluated the ways in which patients interpreted, understood and coped with unpleasant symptoms as well as the support and reactions from significant others to their symptoms. Subjects also participated in an experimental task designed to elicit physical sensations. Following the task, subjects were interviewed regarding cognitions and symptoms associated with the task. Results indicated that both patient groups had significantly greater physical and emotional symptomatology than healthy controls. The IBS patients were largely indistinguishable from the Crohn's patients, except that IBS patients were more likely to perceive their condition as more serious than Crohn's patients, and reported less personal control and responsibility in managing their symptoms. IBS patients also perceived far less social support from individuals close to them than did the Crohn's patients. Both IBS and Crohn's patients engaged in greater dysfunctional cognitive activity than did the controls during the experimental task. While anxiety, depression and coping attempts did not distinguish between patient groups, they were significantly associated with the amount of disability in daily activities regardless of diagnosis. These results suggest that the uncertain etiology of IBS may create additional sources of stress for the IBS patient. Consequently IBS patients may be more prone to misinterpret their IBS as a serious health threat and feel less able to control their symptoms. Furthermore, because of the uncertain etiology, the IBS patient may receive less support from significant others, thereby compounding stress and further taxing coping efforts. Our findings suggest that rather than a psychologic/psychiatric problem the IBS is better viewed as a medical problem within a biopsychosocial context. Psychosocial factors play a crucial role in the manifestation of disability regardless of the nature of the disease. However, the IBS is a unique medical problem in that the patient is placed at risk for stressors related to the uncertainty of the symptoms and the reactions of others.

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Wang, Linghan. "Race Moderates the Motivational Processing of Anti-Smoking PSAs." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1397734531.

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Cadieux, Geneviève. "Assessing and improving the accuracy of surveillance case definitions using administrative data." Thesis, McGill University, 2011. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=103456.

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BACKGROUND Keeping pace with the rapidly evolving demands of infectious disease monitoring requires constant advances in surveillance methodology and infrastructure. A promising new method is syndromic surveillance, where health department staff, assisted by automated data acquisition and statistical alerts, monitor health indicators in near real-time. Several syndromic surveillance systems use diagnoses in administrative databases. However, physician claim diagnoses are not audited, and the effect of diagnostic coding variation on surveillance case definitions is not known. Furthermore, syndromic surveillance systems are limited by high false-positive (FP) rates. Almost no effort has been made to reduce FP rates by improving the positive predictive value (PPV) of surveilled data. OBJECTIVES 1) To evaluate the feasibility of identifying syndrome cases using diagnoses in physician claims. 2) To assess the accuracy of syndrome definitions based on diagnoses in physician claims. 3) To identify physician, patient, encounter and billing characteristics associated with the PPV of syndrome definitions. METHODS & RESULTS STUDY 1: We focused on a subset of diagnoses from a single syndrome (respiratory). We compared cases and non-cases identified from physician claims to medical charts. A convenience sample of 9 Montreal-area family physicians participated. 3,526 visits among 729 patients were abstracted from medical charts and linked to physician claims. The sensitivity and PPV of physician claims for identifying respiratory infections were 0.49, 95%CI (0.45, 0.53) and 0.93, 95%CI (0.91, 0.94). This pilot work demonstrated the feasibility of the proposed method and contributed to planning a full-scale validation of several syndrome definitions. STUDY 2: We focused on 5 syndromes: fever, gastrointestinal, neurological, rash, and respiratory. We selected a random sample of 3,600 physicians practicing in the province of Quebec in 2005-2007, then a stratified random sample of 10 visits per physician from their claims. We obtained chart diagnoses for all sampled visits through double-blinded chart reviews. Sensitivity, specificity, PPV, and negative predictive value (NPV) of syndrome definitions based on diagnoses in physician claims were estimated by comparison to chart review. 1,098 (30.5%) physicians completed the chart review and 10,529 visits were validated. The sensitivity of syndrome definitions ranged from 0.11, 95%CI (0.10, 0.13) for fever to 0.44, 95%CI (0.41, 0.47) for respiratory syndrome. The specificity and NPV were high for all syndromes. The PPV ranged from 0.59, 95%CI (0.55, 0.64) for fever to 0.85, 95%CI (0.83, 0.88) for respiratory syndrome. STUDY 3: We focused on the 4,330 syndrome cases identified from the claims of the 1,098 physicians who participated in study 2. We estimated the association between claim-chart agreement and physician, patient, encounter and billing characteristics using multivariate logistic regression. The likelihood of the medical chart agreeing with the physician claim about the presence of a syndrome was higher when the physician had billed many visits for the same syndrome recently (RR per 10 visits, 1.05; 95%CI, 1.01-1.08), had a lower workload (RR per 10 claims, 0.93; 95%CI, 0.90-0.97), and when the patient was younger (RR per 5 years, 0.96; 95%CI, 0.94-0.97) and less socially deprived (RR most vs least deprived, 0.76; 95%CI, 0.60-0.95). CONCLUSIONS This was the first population-based validation of syndromic surveillance case definitions based on diagnoses in physician claims. We found that the sensitivity of syndrome definitions was low, the PPV was moderate to high, and the specificity and NPV were high. We identified several physician, patient, encounter and billing characteristics associated with the PPV of syndrome definitions, many of which are readily accessible to public health departments and could be used to reduce the FP rate of syndromic surveillance systems. CONTEXTE La surveillance des maladies infectieuses est un défi en constante évolution et un progrès continu au niveau des méthodes et des infrastructures est nécessaire pour répondre à la demande. Une nouvelle approche est la surveillance syndromique, où le personnel de santé publique, assisté de collecte automatisée de données et d'alertes statistiques, surveille des indicateurs de santé en temps quasi-réel. Plusieurs systèmes de surveillance syndromique s'appuient sur les diagnostics issus de bases de données administratives. Parce que ces codes de diagnostics ne font pas l'objet d'audits, l'effet de variations dans leur codage sur les définitions syndromiques demeure inconnu. OBJECTIFS 1) Évaluer la faisabilité d'identifier des syndromes à partir des diagnostics issus des services facturés par les médecins. 2) Évaluer l'exactitude de définitions syndromiques basées sur les diagnostics issus des services facturés par les médecins.3) Identifier les caractéristiques du médecin, du patient, de la rencontre médecin-patient et du mode de facturation associées au coefficient de prédiction positif (CPP) des définitions syndromiques. MÉTHODES & RÉSULTATS ÉTUDE 1: Cette étude a porté sur un seul syndrome (respiratoire). Nous avons comparés les cas positifs et négatifs identifiés à partir de la facturation, aux dossiers médicaux. Un échantillon de 9 médecins généralistes Montréalais a été utilisé. Les diagnostics de 3 526 visites effectuées par 729 patients ont été extraits des dossiers médicaux, et reliés à la facturation. La sensibilité et le CPP des diagnostics d'infection respiratoire issus de la facturation étaient 0.49 et 0.93. Cette étude de faisabilité a permis la planification d'une validation à grande-échelle de plusieurs définitions syndromiques. ÉTUDE 2: Cette étude a porté sur 5 syndromes: fièvre, gastro-intestinal, neurologique, cutané et respiratoire. Nous avons sélectionné aléatoirement 3600 médecins pratiquant au Québec en 2005-2007 et, parmi tous les services facturés, 10 visites par médecin. Pour chaque visite, le diagnostic du dossier médical a été obtenu grâce à une révision de dossier à double insu. La sensibilité, la spécificité, le CPP et le coefficient prédictif négatif (CPN) des définitions syndromiques basées sur les diagnostics issus de la facturation ont été estimés. 1098 (30.5%) médecins ont participé à l'étude et 10529 visites ont été validées. La sensibilité des définitions syndromiques variait de 0.11 pour la fièvre à 0.44 pour le syndrome respiratoire. La spécificité et le CPN étaient élevés pour tous les syndromes. Le CPP variait de 0.59 pour la fièvre à 0.85 pour le syndrome respiratoire. ÉTUDE 3: Nous avons restreint notre échantillon aux 4330 visites des 1098 médecins de l'étude 2 où le diagnostic de la facturation correspondait à l'un des syndromes. Nous avons utilisé une régression logistique multi-variée afin d'estimer l'association entre l'accord facturation-dossier et les caractéristiques du médecin, du patient, de la rencontre médecin-patient et du mode de facturation. La probabilité que le dossier médical confirme un syndrome présent selon la facturation était plus élevée lorsque le médecin avait facturé plusieurs visites pour le même syndrome récemment, avait une charge de travail moindre, et lorsque le patient était plus jeune et moins défavorisé socialement. CONCLUSIONS Cette étude a été la première validation à grande-échelle de définitions syndromiques basées sur les diagnostics issus des services facturés par les médecins. Nous avons découvert que la sensibilité de ces définitions est faible, le CPP varie de moyen à élevé, et la spécificité et le CPN sont élévés. Nous avons identifiés maintes caractéristiques du médecin, du patient, de la rencontre médecin-patient et du mode de facturation associées au CPP des définitions syndromiques, dont plusieurs sont accessibles aux agences de santé publique et pourraient être utilisées pour améliorer les systèmes de surveillance syndromique.

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Brain, Damien, and mikewood@deakin edu au. "Learning from large data : Bias, variance, sampling, and learning curves." Deakin University. School of Information Technology, 2003. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20050728.095343.

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One of the fundamental machine learning tasks is that of predictive classification. Given that organisations collect an ever increasing amount of data, predictive classification methods must be able to effectively and efficiently handle large amounts of data. However, it is understood that present requirements push existing algorithms to, and sometimes beyond, their limits since many classification prediction algorithms were designed when currently common data set sizes were beyond imagination. This has led to a significant amount of research into ways of making classification learning algorithms more effective and efficient. Although substantial progress has been made, a number of key questions have not been answered. This dissertation investigates two of these key questions. The first is whether different types of algorithms to those currently employed are required when using large data sets. This is answered by analysis of the way in which the bias plus variance decomposition of predictive classification error changes as training set size is increased. Experiments find that larger training sets require different types of algorithms to those currently used. Some insight into the characteristics of suitable algorithms is provided, and this may provide some direction for the development of future classification prediction algorithms which are specifically designed for use with large data sets. The second question investigated is that of the role of sampling in machine learning with large data sets. Sampling has long been used as a means of avoiding the need to scale up algorithms to suit the size of the data set by scaling down the size of the data sets to suit the algorithm. However, the costs of performing sampling have not been widely explored. Two popular sampling methods are compared with learning from all available data in terms of predictive accuracy, model complexity, and execution time. The comparison shows that sub-sampling generally products models with accuracy close to, and sometimes greater than, that obtainable from learning with all available data. This result suggests that it may be possible to develop algorithms that take advantage of the sub-sampling methodology to reduce the time required to infer a model while sacrificing little if any accuracy. Methods of improving effective and efficient learning via sampling are also investigated, and now sampling methodologies proposed. These methodologies include using a varying-proportion of instances to determine the next inference step and using a statistical calculation at each inference step to determine sufficient sample size. Experiments show that using a statistical calculation of sample size can not only substantially reduce execution time but can do so with only a small loss, and occasional gain, in accuracy. One of the common uses of sampling is in the construction of learning curves. Learning curves are often used to attempt to determine the optimal training size which will maximally reduce execution time while nut being detrimental to accuracy. An analysis of the performance of methods for detection of convergence of learning curves is performed, with the focus of the analysis on methods that calculate the gradient, of the tangent to the curve. Given that such methods can be susceptible to local accuracy plateaus, an investigation into the frequency of local plateaus is also performed. It is shown that local accuracy plateaus are a common occurrence, and that ensuring a small loss of accuracy often results in greater computational cost than learning from all available data. These results cast doubt over the applicability of gradient of tangent methods for detecting convergence, and of the viability of learning curves for reducing execution time in general.

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Moreira, Gerardo Jose. "Instilling Positive Beliefs about Organ Donation| An Information Processing Approach." Thesis, The University of Texas at El Paso, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10683171.

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The number of those seeking a kidney donation in the United States continues to increase while the number of donors is not growing at the same rate (U.S. Department of Health and Human Services USDHHS, 2010). The lack of donations is more prevalent in low health literate communities which suffer from misinformation and ultimately negative beliefs toward organ donation. Thus, it is important to understand how marketing efforts can effectively change individuals’ beliefs about organ donation. Drawing on the Self-Determination Theory and Schema Theory, I proposed that the effectiveness of health education programs, which is to motivate individuals to be involved with organ donation, can be increased by creating interventions that engage individuals’ senses. I used the term sensory activation to capture the number of senses being activated (visual, auditory, and kinesthetic). I proposed that sensory activation is related to message recall and motivation. According to Schema Theory, sensory cues are batches of information that can be stored in memory, thus affecting recall. The more senses involved in an experience, the more nodes of information available for recall, and the higher the likelihood that recall will affect motivation structures. Thus, I hypothesized that the relationship between sensory activation and motivation is positive, and, yet, mediated by recall. In addition, research findings in sensory marketing suggest that the relationship between sensory strength and recall should be stronger for individuals with low, rather than high, health literacy. Low health literate individuals lack the cognitive ability to understand and interpret the information provided, hence, sensorial information allows them to recall the message. For high health literate individuals, understanding the message is relatively easier, hence, the addition of sensorial cues may lead to disinterest. That is, high health literate individuals may disregard additional sensorial information due to redundancy. Therefore, I hypothesized that the relationship between sensory activation, recall, and beliefs will be stronger for low, rather than for high, literacy individuals. Lastly, Schema Theory suggests that individuals tend to simplify multiple information cues and form abstract knowledge structures. Instead of storing (and recalling) multiple information cues independently, individuals convert multiple pieces of information into abstract concepts. This abstraction process increases over time because it is easier to remember concepts rather than multiple batches of detailed information. Thus, I hypothesized that, in the long term, recall of specific information will be higher for individuals with high, rather than low, health literacy. High health literacy individuals can incorporate specific information into existing knowledge structures. Low health literacy individuals lack knowledge structures to further develop. Accordingly, low health literacy individuals will create an abstract representation of the experience. That is, low health literacy individuals will not remember specific information, but will remember the event in broad terms (abstractly). Consequently, overtime, the motivation will be stronger for high, rather than for low, health literacy individuals. I tested my hypotheses by conducting a 3 (Sensory Strength: sight, sight + hearing, sight + hearing + touch) × 2 (Literacy: low, high), between-subjects factorial design. Sensory activation was manipulated, while health literacy was measured. I conducted the study in three phases. Phase 1 included a questionnaire of health information, motivation, beliefs, learning styles, and psychological measures prior to the experiment. Phase 2 included the manipulation of sensory activation and a questionnaire including manipulation checks and dependent variables. Phase 3 included a follow-up questionnaire two weeks later. This dissertation, although having non-significant findings, adds to marketing literature by involving information processing and testing the role of sensory cues in message recall and motivation. Also, this work sheds light on the interplay between individual differences and the cognitive processing of sensory cues. To practitioners, this study provides normative recommendations regarding the design health interventions. Specifically, it is suggested that interventions should activate several sensory cues in order to enable short-term recall among low health literate consumers. Similarly, trends in the data suggest that health educators increase health literacy, as health literacy is a predictor for long-term recall and behavior modification. Finally, this work informs advertising professionals on how to apply sensory marketing in health promotion.

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Thomas, Godwin Dogara Ayenajeh. "A virtual-community-centric model for coordination in the South African public sector." Thesis, Nelson Mandela Metropolitan University, 2014. http://hdl.handle.net/10948/d1021073.

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Organizations face challenges constantly owing to limited resources. As such, to take advantage of new opportunities and to mitigate possible risks they look for new ways to collaborate, by sharing knowledge and competencies. Coordination among partners is critical in order to achieve success. The segmented South African public sector is no different. Driven by the desire to ensure proper service delivery in this sector, various government bodies and service providers play different roles towards the attainment of common goals. This is easier said than done, given the complexity of the distributed nature of the environment. Heterogeneity, autonomy, and the increasing need to collaborate provoke the need to develop an integrative and dynamic coordination support service system in the SA public sector. Thus, the research looks to theories/concepts and existing coordination practices to ground the process of development. To inform the design of the proposed artefact the research employs an interdisciplinary approach championed by coordination theory to review coordination-related theories and concepts. The effort accounts for coordination constructs that characterize and transform the problem and solution spaces. Thus, requirements are explicit towards identifying coordination breakdowns and their resolution. Furthermore, how coordination in a distributed environment is supported in practice is considered from a socio-technical perspective in an effort to account holistically for coordination support. Examining existing solutions identified shortcomings that, if addressed, can help to improve the solutions for coordination, which are often rigidly and narrowly defined. The research argues that introducing a mediating technological artefact conceived from a virtual community and service lenses can serve as a solution to the problem. By adopting a design-science research paradigm, the research develops a model as a primary artefact to support coordination from a collaboration standpoint. The suggestions from theory and practice and the unique case requirement identified through a novel case analysis framework form the basis of the model design. The proposed model support operation calls for an architecture which employs a design pattern that divides a complex whole into smaller, simpler parts, with the aim of reducing the system complexity. Four fundamental functions of the supporting architecture are introduced and discussed as they would support the operation and activities of the proposed collaboration lifecycle model geared towards streamlining coordination in a distributed environment. As part of the model development knowledge contributions are made in several ways. Firstly, an analytical instrument is presented that can be used by an enterprise architect or business analyst to study the coordination status quo of a collaborative activity in a distributed environment. Secondly, a lifecycle model is presented as meta-process model with activities that are geared towards streamlining the coordination of dynamic collaborative activities or projects. Thirdly, an architecture that will enable the technical virtual community-centric, context-aware environment that hosts the process-based operations is offered. Finally, the validation tool that represents the applied contribution to the research that promises possible adaptation for similar circumstances is presented. The artefacts contribute towards a design theory in IS research for the development and improvement of coordination support services in a distributed environment such as the South African public sector.

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Sadeghzadeh, Seyedehsaloumeh. "Optimal Data-driven Methods for Subject Classification in Public Health Screening." Diss., Virginia Tech, 2019. http://hdl.handle.net/10919/101611.

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Biomarker testing, wherein the concentration of a biochemical marker is measured to predict the presence or absence of a certain binary characteristic (e.g., a disease) in a subject, is an essential component of public health screening. For many diseases, the concentration of disease-related biomarkers may exhibit a wide range, particularly among the disease positive subjects, in part due to variations caused by external and/or subject-specific factors. Further, a subject's actual biomarker concentration is not directly observable by the decision maker (e.g., the tester), who has access only to the test's measurement of the biomarker concentration, which can be noisy. In this setting, the decision maker needs to determine a classification scheme in order to classify each subject as test negative or test positive. However, the inherent variability in biomarker concentrations and the noisy test measurements can increase the likelihood of subject misclassification. We develop an optimal data-driven framework, which integrates optimization and data analytics methodologies, for subject classification in disease screening, with the aim of minimizing classification errors. In particular, our framework utilizes data analytics methodologies to estimate the posterior disease risk of each subject, based on both subject-specific and external factors, coupled with robust optimization methodologies to derive an optimal robust subject classification scheme, under uncertainty on actual biomarker concentrations. We establish various key structural properties of optimal classification schemes, show that they are easily implementable, and develop key insights and principles for classification schemes in disease screening. As one application of our framework, we study newborn screening for cystic fibrosis in the United States. Cystic fibrosis is one of the most common genetic diseases in the United States. Early diagnosis of cystic fibrosis can substantially improve health outcomes, while a delayed diagnosis can result in severe symptoms of the disease, including fatality. We demonstrate our framework on a five-year newborn screening data set from the North Carolina State Laboratory of Public Health. Our study underscores the value of optimization-based approaches to subject classification, and show that substantial reductions in classification error can be achieved through the use of the proposed framework over current practices. Doctor of Philosophy

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Li, Guilin 1973. "Re-analyses of Framingham data using time-dependent covariates." Thesis, McGill University, 1999. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=29907.

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I propose a new approach, based on time-dependent covariates, to assess the impact of within-subject changes in predictors on subsequent mortality, and apply it to reevaluate the impact of changes in serum cholesterol and smoking status on the coronary heart mortality in the Framingham Heart Study. Time-dependent covariates, representing updated risk factor value or its changes from either the baseline or the most recent measurement are included in two types of multivariable Cox regression analyses. The results reveal that in order to avoid confounding of the effects of changes in risk factor, the model should include a time-dependent variable identifying subjects who developed coronary disease during the follow-up. After adjusting for this variable, a within-subject decrease in cholesterol was associated with a significant reduction of corollary mortality, in contrast to the results of previous studies that did not prevent such confounding.

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Pentaris, Fragkiskos. "Digital signal processing for structural health monitoring of buildings." Thesis, Brunel University, 2014. http://bura.brunel.ac.uk/handle/2438/10560.

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Structural health monitoring (SHM) systems is a relatively new discipline, studying the structural condition of buildings and other constructions. Current SHM systems are either wired or wireless, with a relatively high cost and low accuracy. This thesis exploits a blend of digital signal processing methodologies, for structural health monitoring (SHM) and develops a wireless SHM system in order to provide a low cost implementation yet reliable and robust. Existing technologies of wired and wireless sensor network platforms with high sensitivity accelerometers are combined, in order to create a system for monitoring the structural characteristics of buildings very economically and functionally, so that it can be easily implemented at low cost in buildings. Well-known and established statistical time series methods are applied to SHM data collected from real concrete structures subjected to earthquake excitation and their strong and weak points are investigated. The necessity to combine parametric and non-parametric approaches is justified and to this direction novel and improved digital signal processing techniques and indexes are applied to vibration data recordings, in order to eliminate noise and reveal structural properties and characteristics of the buildings under study, that deteriorate due to environmental, seismic or anthropogenic impact. A characteristic and potential harming specific case study is presented, where consequences to structures due to a strong earthquake of magnitude 6.4 M are investigated. Furthermore, is introduced a seismic influence profile of the buildings under study related to the seismic sources that exist in the broad region of study.

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Xiao, Tao. "Bayesian Threshold Regression for Current Status Data with Informative Censoring." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1438272888.

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Mantoro, Teddy. "Distributed support for intelligent environments /." View thesis entry in Australian Digital Theses Program, 2006. http://thesis.anu.edu.au/public/adt-ANU20070123.150814/index.html.

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Dewart, Courtney McAlear. "Evaluating Risk Factors for Antimicrobial Resistance Using Electronic Health Record Data." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1555234514305512.

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Cousins, Margaret. "Impact of the Healthstyles health promotion program on health care utilization: A secondary analysis of data." Thesis, University of Ottawa (Canada), 1994. http://hdl.handle.net/10393/6652.

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Healthstyles was a community based health promotion program that ran in Ottawa from 1982 to 1984. This program provided an opportunity to assess the effects of health promotion on health behaviours and use of health care services through a quasi-experimental design. Primary analyses of questionnaire responses have shown a number of positive behavioural outcomes. For the secondary analysis, data on health care use 6 months before, 18 months during and 6 months after the program were obtained from Ontario's universal health insurance plan (OHIP). These data were available for 520 volunteer participants and 932 matched controls. Participants and controls were matched on sex, age (within 5 years), education level (2 categories), stress (3 levels), smoking status and an aggregate risk score. Controlling for baseline differences through analysis of covariance, program participants had higher costs and number of visits for ambulatory care during the first year (p 0.01) and second year (p 0.05) after entry into the program. Within ambulatory care, participants used significantly more diagnostic services than controls during both years of follow-up. Participants were also more likely to use counselling and psychotherapy services in year 1 (RR 1.53, 95% CI 1.28, 1.81) and year 2 (RR 1.57, 95% CI 1.31, 1.89). There were no differences between participants and controls in visits for medical consultations and assessments, preventive services or surgical services. These results suggest that health promotion may lead to increased costs and use of ambulatory services, at least over the short-term. However, these costs may be offset over a longer follow-up period if health promotion successfully reduces the incidence of chronic illness. Since the sample population was relatively young and had positive health behaviours at baseline, compared to the general population, the results may not apply to other, less healthy populations.

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Gallagher, Naomh. "Diabetes in Northern Ireland : using routine health care data to inform public health care policy." Thesis, Queen's University Belfast, 2013. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.601482.

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Diabetes is a leading cause of morbidity and mortality around the world, and the prevalence is increasing dramatically. Rather surprisingly, there is no consensus regarding the burden of diabetes in Northern Ireland. This thesis outlines the creation and utilisation of a novel centrally collated population wide dataset of dispensed prescriptions known as the Enhanced Prescribing Data base (EPO). This was successfully used, together with linkage of other demographic and health-related data, to provide estimates of the prevalence, incidence and changing prevalence of diabetes in Northern Ireland over a three year period, and of the associated relative mortality risk for patients with diabetes. Through further linkage to unique and individual-level indicators of socioeconomic status, a comprehensive picture of the differential burden of diabetes across society was produced. Variation related to geography, demographics, socioeconomic variables, and over time was investigated. In addition, the thesis demonstrates how routine administrative data can be used to investigate the relationship between health policy and diabetes ca re. This was outlined in two studies; the first, using a time series analysis, showed how the introduction of financial incentives for GPs in the UK, , , through the Quality and Outcomes Framework (QOF) initiative changed the care of t he approximately 30% of patients with type 2 diabetes who are usually managed non• pharmacologically. The second study demonstrated how use of routine data can be used to undertake comparative analysis of patients with diabetes in Northern Ireland and the Republic of Ireland (two similar populations with distinct health systems) to the potentially mutual benefit of both jurisdictions. This thesis provides both a novel methodology to estimate diabetes in Northern Ireland, and a number of unique examples of how administrative datasets and record linkage can be successfully utilised to answer important and policy Relevant questions in diabetes and heather services research.

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Pardue, Miranda Taylor. "Comparing Heatwave Related Mortality Data from Distressed Counties to Affluent Counties in Central and Southern Central Appalachia." Digital Commons @ East Tennessee State University, 2020. https://dc.etsu.edu/honors/583.

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The Appalachian Mountains are home to some of the most culturally rich places in the United States, but also some of the most impoverished communities as well. Several recent events support climate change across the globe. It is expected that Appalachian communities may suffer more dire consequences, as many communities lack strategies to help relieve some of the worst effects of climate change. Heatwaves are predicted to increase in duration and frequency over time, and communities that are not well prepared for the damaging effects of heatwaves can suffer unduly. This study aims to quantify the likelihood that people living in economically distressed counties in the Central and Southern Central regions of Appalachia will face heatwave related mortality more intensely than those who live in more affluent counties in the same regions. Twelve counties from each socioeconomic group have been selected based on the county economic status to analyze climate and mortality data over thirty-eight years starting in 1981 and ending in 2018. Data was collected during the warm season for each county, May 1st to September 30th, and compared to the mortality data from the same county during the same warm season. This study used all-cause mortality numbers from each of the twenty-four counties for the mortality data. The relative risk for each county in both the distressed and affluent categories was calculated. The average relative risk for each socioeconomic status were then compared. The results of this study did not show statistical significance in the likelihood that being in a socioeconomically distressed county increases one's chances of succumbing to heatwave related mortality in the Central and Southern Central regions of Appalachia. More research with larger sample sizes and more attention paid to the factors driving socioeconomic status is needed to better assess the relationship of heatwave mortality to socioeconomic status.

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Baldassari, James D. "Design and evaluation of a public resource computing framework." Link to electronic thesis, 2006. http://www.wpi.edu/Pubs/ETD/Available/etd-042006-225855/.

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Labrecque, Jeremy. "Estimating health-selective migration in patients with systemic lupus erythematosus or Sjogren's from administrative data." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114191.

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Canadian public health agencies have a mandate to monitor the prevalence, incidence and patterns of chronic disease. These agencies are increasingly using administrative health data for these purposes. However, valid use of administrative data for chronic disease surveillance requires an understanding of some inherent limitations. Health-selective migration, which occurs when people migrate differentially by health status, is a limitation that has not been estimated in administrative data sources. To investigate this issue, we estimated health-selective migration in a cohort of systemic lupus erythematosus (SLE) and Sjogren's patients, identified from physician and hospital claims databases in Quebec and compared them to rates in an age and sex frequency-matched sample from Montreal, Quebec using hierarchical logistic regression. The association between disease and migration was modified by both age and disease duration. Both SLE and Sjogren's patients migrated less than controls when young. For example, 30-year-old SLE (OR 0.54, 95% CrI 0.45-0.64) and Sjogren's (OR 0.41, 95% CrI 0.28-0.56) patients with two years of disease duration had lower odds of moving than frequency-matched controls. Above age 50, the odds of migration in SLE and Sjogren's patients was comparable or slightly higher than in controls. Patients at age 70 with two years of disease duration had an OR of moving of 1.29 (95% CrI 1.04-1.58) in SLE and 1.09 (95% CrI 0.81-1.42) in Sjogren's. The associations between migration and disease duration in SLE and Sjogren's were qualitatively different. One year of SLE duration was associated with an OR of 0.96 (95% CrI 0.93-0.98) and one year of Sjogren's duration was associated with an OR of 1.05 (95% CrI 1.00-1.10). Results were similar when using SLE and Sjogren's patients pre-diagnosis as the control and when looking at migration on a regional scale. Overall, SLE and Sjogren's have an impact on migration rates which varies by age, disease and disease duration. Les organismes canadiens de santé publique ont le mandat de surveiller la prévalence, incidence, et les tendances des maladies chroniques dans notre pays. De plus en plus, ces agences utilisent des bases de données administratives sur la santé à ces fins. Cependant, l'utilisation valable de ces sources de données pour la surveillance des maladies chroniques exige une compréhension de certaines limites inhérentes, en particulier la migration sélective par l'état de santé, ce qui se produit lorsque les gens migrent de façon différente du à leur état de santé. Nous avons effectué une évaluation des déménagements chez des patients ayant le lupus érythémateux disséminé ou le syndrome de Sjogren's tel qu'identifiés dans les données des réclamations des médecins et des hôpitaux du Québec. La régression logistique hiérarchique a été utilisée pour comparer les taux de migration chez des patients atteints de lupus ou de Sjogren's aux taux de déménagement dans un échantillon de concordance des fréquences par âge et par sexe de la population de Montréal.Dans notre échantillon, l'association entre les maladies et la migration a démontré des modifications par l'âge du patient et la durée de sa maladie. Les patients lupiques ou ayant le Sjogren's déménagent moins quand ils sont plus jeunes. Par exemple, à 30 ans et atteint de l'une de ces maladies depuis deux ans les patients lupiques (RC: 0.54, intervalle crédible (ICr) 95% 0.45-0.6) et ceux atteints de Sjogren's (RC: 0.41, ICr 95% 0.28-0.56) ont des cotes de déménagement moins élevés que ceux du groupe témoin. Par contre, à 50 ans et plus, les cotes de migration des patients lupiques et ayant le Sjogren's sont comparables et même légèrement supérieures à celles du groupe témoin. Les patients âgées de 70 ans étant malades depuis 2 ans ont un rapport de cotes de déplacement de 1,29 (ICr 95%: 1,04-1,58) pour ceux atteints du lupus et de 1,09 (ICr 95%, 0,81-1,42) pour ceux ayant le Sjogren's. Aussi, l'association entre la migration et la durée de la maladie était qualitativement différente entre les patients lupiques et les patients atteints de Sjogren's. Par exemple, les patients ayant le lupus depuis un an ont montrés un rapport de cotes de 0,96 (ICr 95%, 0,93-098) et les patients atteint de Sjogren's ont montrés un rapport de cotes de 1,05 (ICr 95% 1,00-1,10) par an de durée de maladie.Les résultats étaient similaires lorsque le groupe témoin était composé de patients qui n'avaient pas encore été diagnostiqués ou lorsqu'on regarde les migrations à l'échelle régionale. Ce mémoire supporte l'idée que les maladies chroniques peuvent affecter les taux de migration et que ceux-ci peuvent varier en fonction de l'âge du patient, de la maladie et de la durée de cette maladie.

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Hockin, James Charles. "A case-control study of risk factors for ectopic pregnancy using routinely collected administrative data." Thesis, University of Ottawa (Canada), 1990. http://hdl.handle.net/10393/5628.

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The potential for using the case-control design with only hospital separation records was explored in a study of ectopic pregnancy. The Saskatchewan Hospital Services Commission hospital morbidity database was used. Cases were women hospitalized for ectopic pregnancy in the years 1984 through 1986. Controls were women hospitalized for any other pregnancy condition. In a case-control study using pregnant controls, the odds ratio is an appropriate estimator of relative risk, conditional on conception. Among the potential risk factors (exposures) represented in the data were tubal surgery, prior ectopic pregnancy, pelvic inflammatory disease, and infertility. Of these, the first two are completely ascertained during the time a woman was resident in Saskatchewan. Under representation of exposures should be non-differential, leading to odds ratios which are biased towards the null. Multiple logistic regression analysis yielded estimates of the odds ratios for acute PID, chronic PID or pelvic adhesions, prior ectopic pregnancy, tubal sterilization, and tubal repair. Of particular interest was the association between ectopic pregnancy and tubal surgery performed in the hope of maintaining or restoring normal tubal function. The attributable risk proportion of ectopic pregnancy due to such surgery was 8.1%. This study design can be used to follow trends in surgical causes of ectopic pregnancy in Canada. (Abstract shortened by UMI.)

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Heffner, Michael D. "Informing Decision-Making for Derailments Involving Hazmat| An Analysis of Phmsa Train Accident Data." Thesis, California State University, Long Beach, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10604290.

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A review of literature suggests that train derailments are a statistically relevant concern. While not all train derailments involve hazardous materials, those that do release chemicals pose a public health threat. This study challenges the decision-making mainstay tool of the hazardous materials response community – the Emergency Response Guidebook (ERG) – and its default strategy of evacuation through quantitative research that evaluates data from train derailments involving the release of hazardous materials. It explores whether there are correlations between a derailment’s variables and evacuation, as well as correlations between the number evacuated and the number of those injured or killed. Secondary data on train derailments from the Pipeline Hazardous Material Safety Administration revealed 358 incidents involving the release of 876 substances between October 12, 1989 through August 10, 2016. The resulting data analysis confirms a certain level of predictability between causal factors and worsening outcomes supporting expansion of decision-making tools in the ERG.

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Yang, Shaojie. "A Data Augmentation Methodology for Class-imbalanced Image Processing in Prognostic and Health Management." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin161375046654683.

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Dissertations / Theses on the topic 'Public health Data processing'

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