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Готові списки джерел за темами / Public health Data processing / Статті в журналах

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Статті в журналах з теми "Public health Data processing"

Автор: Grafiati

Опубліковано: 4 червня 2021

Оновлено: 19 лютого 2022

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1

Taylor, Mark J., and Tess Whitton. "Public Interest, Health Research and Data Protection Law: Establishing a Legitimate Trade-Off between Individual Control and Research Access to Health Data." Laws 9, no. 1 (February 14, 2020): 6. http://dx.doi.org/10.3390/laws9010006.

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The United Kingdom’s Data Protection Act 2018 introduces a new public interest test applicable to the research processing of personal health data. The need for interpretation and application of this new safeguard creates a further opportunity to craft a health data governance landscape deserving of public trust and confidence. At the minimum, to constitute a positive contribution, the new test must be capable of distinguishing between instances of health research that are in the public interest, from those that are not, in a meaningful, predictable and reproducible manner. In this article, we

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2

Siriwardena, N., and M. Dharmawardhana. "Real time data collection and processing using mobile technology: A public health perspective." Sri Lanka Journal of Bio-Medical Informatics 1 (October 24, 2011): 7. http://dx.doi.org/10.4038/sljbmi.v1i0.3539.

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3

Rodriguez Ayuso, Juan Francisco. "Processing of personal data relating to the health of the data subject in a pandemic situation." Glimpse 22, no. 1 (2021): 95–99. http://dx.doi.org/10.5840/glimpse202122115.

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This study offers a systematic, exhaustive and updated investigation of the declaration of the state of alarm and the processing of personal data relating to the health of citizens affected and/or potentially affected by the exceptional situation resulting from COVID-19. Specifically, it analyses the distinction between the state of alarm and the states of exception and siege and the possible effect on the fundamental right to the protection of personal data in exceptional health crisis situations and the effects that this declaration may have on the applicable regulations, issued, at a Commun

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4

Jones, Julie Miller. "Food processing: criteria for dietary guidance and public health?" Proceedings of the Nutrition Society 78, no. 1 (September 25, 2018): 4–18. http://dx.doi.org/10.1017/s0029665118002513.

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The NOVA food categorisation recommends ‘avoiding processed foods (PF), especially ultra-processed foods (UPF)’ and selecting minimally PF to address obesity and chronic disease. However, NOVA categories are drawn using non-traditional views of food processing with additional criteria including a number of ingredients, added sugars, and additives. Comparison of NOVA's definition and categorisation of PF with codified and published ones shows limited congruence with respect to either definition or food placement into categories. While NOVA studies associate PF with decreased nutrient density, o

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5

Becker, Regina, Adrian Thorogood, Johan Ordish, and Michael J. S. Beauvais. "COVID-19 Research: Navigating the European General Data Protection Regulation." Journal of Medical Internet Research 22, no. 8 (August 27, 2020): e19799. http://dx.doi.org/10.2196/19799.

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Researchers must collaborate globally to rapidly respond to the COVID-19 pandemic. In Europe, the General Data Protection Regulation (GDPR) regulates the processing of personal data, including health data of value to researchers. Even during a pandemic, research still requires a legal basis for the processing of sensitive data, additional justification for its processing, and a basis for any transfer of data outside Europe. The GDPR does provide legal grounds and derogations that can support research addressing a pandemic, if the data processing activities are proportionate to the aim pursued

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6

Cummings, Stuart W. "Distributed Databases for Clinical Data Processing." Drug Information Journal 27, no. 4 (October 1993): 949–56. http://dx.doi.org/10.1177/009286159302700403.

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7

Pimazzoni, Monica. "Global Data Management: A Winning Approach to Clinical Data Processing." Drug Information Journal 32, no. 2 (April 1998): 569–71. http://dx.doi.org/10.1177/009286159803200230.

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8

Woods, Valerie. "Musculoskeletal disorders and visual strain in intensive data processing workers." Occupational Medicine 55, no. 2 (March 1, 2005): 121–27. http://dx.doi.org/10.1093/occmed/kqi029.

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9

Determann, Lothar. "Healthy Data Protection." Michigan Technology Law Review, no. 26.2 (2020): 229. http://dx.doi.org/10.36645/mtlr.26.2.healthy.

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Modern medicine is evolving at a tremendous speed. On a daily basis, we learn about new treatments, drugs, medical devices, and diagnoses. Both established technology companies and start-ups focus on health-related products and services in competition with traditional healthcare businesses. Telemedicine and electronic health records have the potential to improve the effectiveness of treatments significantly. Progress in the medical field depends above all on data, specifically health information. Physicians, researchers, and developers need health information to help patients by improving diag

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10

Wu, Hong Jiang, Xiang Yang Liu, Hai Yan Zhao, and Xiao Ting Li. "Research on Public Health Service Systems Based on Cloud Computing." Applied Mechanics and Materials 687-691 (November 2014): 2849–52. http://dx.doi.org/10.4028/www.scientific.net/amm.687-691.2849.

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This research is aimed at building a real time public fitness service system, with massive data storage and processing ability, to meet the public fitness service demand. In this research, we focus on the system positioning, cloud delegation model, service model, service content and operation mechanism of the fitness service system. Method used was system analysis method.

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11

Bertalya, Bertalya, Prihandoko Prihandoko, Lilis Setyowati, Febrian Iftikhar Irawan, and Syahifa Rahmita Irlianti. "Formulation of city health development index using data mining." Indonesian Journal of Electrical Engineering and Computer Science 23, no. 1 (July 1, 2021): 362. http://dx.doi.org/10.11591/ijeecs.v23.i1.pp362-369.

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Every five years Public Health Research publishes a Public Health Development Index that describes public health in Indonesia. The Public Health Development Index is measured using data from the Public Health Research and the National Socio-Economic Survey, and the Village Potential Survey which is obtained by surveying from sampling data. In fact, the Provincial and City Health Offices have health profile data reports every year. For this reason, this study analyzes existing health profile data using data mining techniques to obtain indicator data that are very influential in formulating the

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12

Sukumar, Sreenivas R., Ramachandran Natarajan, and Regina K. Ferrell. "Quality of Big Data in health care." International Journal of Health Care Quality Assurance 28, no. 6 (July 13, 2015): 621–34. http://dx.doi.org/10.1108/ijhcqa-07-2014-0080.

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Purpose – The current trend in Big Data analytics and in particular health information technology is toward building sophisticated models, methods and tools for business, operational and clinical intelligence. However, the critical issue of data quality required for these models is not getting the attention it deserves. The purpose of this paper is to highlight the issues of data quality in the context of Big Data health care analytics. Design/methodology/approach – The insights presented in this paper are the results of analytics work that was done in different organizations on a variety of h

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13

Unwin, Elizabeth, James Codde, Louise Gill, Suzanne Stevens, and Timothy Nelson. "The WA Hospital Morbidity Data System: An Evaluation of its Performance and the Impact of Electronic Data Transfer." Health Information Management 26, no. 4 (December 1996): 189–92. http://dx.doi.org/10.1177/183335839702600407.

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This paper evaluates the performance of the Hospital Morbidity Data System, maintained by the Health Statistics Branch (HSB) of the Health Department of Western Australia (WA). The time taken to process discharge summaries was compared in the first and second halves of 1995, using the number of weeks taken to process 90% of all discharges and the percentage of records processed within four weeks as indicators of throughput. Both the hospitals and the HSB showed improvements in timeliness during the second half of the year. The paper also examines the impact of a recently introduced electronic

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14

Leeson, William, Adam Resnick, Daniel Alexander, and John Rovers. "Natural Language Processing (NLP) in Qualitative Public Health Research: A Proof of Concept Study." International Journal of Qualitative Methods 18 (January 1, 2019): 160940691988702. http://dx.doi.org/10.1177/1609406919887021.

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Qualitative data-analysis methods provide thick, rich descriptions of subjects’ thoughts, feelings, and lived experiences but may be time-consuming, labor-intensive, or prone to bias. Natural language processing (NLP) is a machine learning technique from computer science that uses algorithms to analyze textual data. NLP allows processing of large amounts of data almost instantaneously. As researchers become conversant with NLP, it is becoming more frequently employed outside of computer science and shows promise as a tool to analyze qualitative data in public health. This is a proof of concept

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15

Arisetty, Murty. "A Team-Based Approach to Clinical Data Processing." Drug Information Journal 19, no. 1 (January 1985): 81–84. http://dx.doi.org/10.1177/009286158501900113.

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16

Leighton, Charles C. "Clinical Data Processing in Retrospect and in Prospect." Drug Information Journal 20, no. 1 (January 1986): 7–15. http://dx.doi.org/10.1177/009286158602000103.

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17

Gillum, Terry L., Robert H. George, and Jack E. Leitmeyer. "An Autoencoder for Clinical and Regulatory Data Processing." Drug Information Journal 29, no. 1 (January 1995): 107–13. http://dx.doi.org/10.1177/009286159502900115.

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18

McDowell, Ian, Margaret Stewart, Betsy Kristjansson, Elizabeth Sykes, Gerry Hill, and Joan Lindsay. "Data Collected in the Canadian Study of Health and Aging." International Psychogeriatrics 13, S1 (February 2001): 29–39. http://dx.doi.org/10.1017/s1041610202007962.

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The Canadian Study of Health and Aging collected data focusing on the epidemiology of dementia, using interviews and questionnaires, clinical and neuropsychological examinations, physical measurements and blood collection, and access to public records such as death certificates, from people 65 and over in community (N = 9,008) institutional settings (N = 1,255). The study produced 12 data sets, including community health interviews, clinical and neuropsychological assessements, risk factor questionnaires, and caregiver interviews. This report describes the data collection and processing proced

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19

Carpenter, Joseph E., Arthur S. Chang, Alvin C. Bronstein, Richard G. Thomas, and Royal K. Law. "Identifying Incidents of Public Health Significance Using the National Poison Data System, 2013–2018." American Journal of Public Health 110, no. 10 (October 2020): 1528–31. http://dx.doi.org/10.2105/ajph.2020.305842.

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Data System. The American Association of Poison Control Centers (AAPCC) and the Centers for Disease Control and Prevention (CDC) jointly monitor the National Poison Data System (NPDS) for incidents of public health significance (IPHSs). Data Collection/Processing. NPDS is the data repository for US poison centers, which together cover all 50 states, the District of Columbia, and multiple territories. Information from calls to poison centers is uploaded to NPDS in near real time and continuously monitored for specific exposures and anomalies relative to historic data. Data Analysis/Disseminatio

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20

Hrzic, Rok, Timo Clemens, Daan Westra, and Helmut Brand. "Comparability in Cross-National Health Research Using Insurance Claims Data: The Cases of Germany and The Netherlands." Das Gesundheitswesen 82, S 01 (November 19, 2019): S83—S90. http://dx.doi.org/10.1055/a-1005-6792.

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Abstract Objective Comparison is a key method in learning about what works in health and healthcare. We discuss the importance of comparability in cross-national health research using health insurance claims data, develop a framework to systematically asses these threats and apply it to the German (DaTraV) and Dutch (Vektis) national-level insurance claims datasets. Methods We propose a framework of threats to the comparability of health insurance claims databases, which includes three domains: (1) representation of populations compared, (2) data sources and data processing and (3) database co

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21

Lee, Edmund W. J., and Kasisomayajula Viswanath. "Big Data in Context: Addressing the Twin Perils of Data Absenteeism and Chauvinism in the Context of Health Disparities Research." Journal of Medical Internet Research 22, no. 1 (January 7, 2020): e16377. http://dx.doi.org/10.2196/16377.

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Recent advances in the collection and processing of health data from multiple sources at scale—known as big data—have become appealing across public health domains. However, present discussions often do not thoroughly consider the implications of big data or health informatics in the context of continuing health disparities. The 2 key objectives of this paper were as follows: first, it introduced 2 main problems of health big data in the context of health disparities—data absenteeism (lack of representation from underprivileged groups) and data chauvinism (faith in the size of data without con

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22

Waterhouse, Andrew L. "Consumer Labels can Convey Polyphenolic Content: Implications for Public Health." Clinical and Developmental Immunology 12, no. 1 (2005): 43–46. http://dx.doi.org/10.1080/10446670410001722249.

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Polyphenolics are a large group of related substances. Many of these, in fact much of that found in food, is composed of processing-derived substances too complex for complete identification. Recent studies have suggested likely benefits for diets high in polyphenols, particular in reducing heart disease mortality, but other benefits have also been suggested. A consumer label based on the major polyphenolic classes is both manageable and fairly informative as most foods do not contain all possible classes. Differences between class member can be significant, but data on individual substances i

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23

Conway, Mike, Mengke Hu, and Wendy W. Chapman. "Recent Advances in Using Natural Language Processing to Address Public Health Research Questions Using Social Media and ConsumerGenerated Data." Yearbook of Medical Informatics 28, no. 01 (August 2019): 208–17. http://dx.doi.org/10.1055/s-0039-1677918.

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Objective: We present a narrative review of recent work on the utilisation of Natural Language Processing (NLP) for the analysis of social media (including online health communities) specifically for public health applications. Methods: We conducted a literature review of NLP research that utilised social media or online consumer-generated text for public health applications, focussing on the years 2016 to 2018. Papers were identified in several ways, including PubMed searches and the inspection of recent conference proceedings from the Association of Computational Linguistics (ACL), the Confe

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24

Miningwa, Alex. "INFLUENCE OF SOURCE OF DATA, INFORMATION FLOWS AND EXCHANGE PLATFORMS ON LEVEL OF HIS FEEDBACK IN PUBLIC HEALTH FACILITIES." American Journal of Data, Information and Knowledge Management 2, no. 1 (August 5, 2021): 43–53. http://dx.doi.org/10.47672/ajdikm.763.

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Purpose: Data collection is the first step of the information process within the health information system, so health information systems are often classified according to data collection method. The general objective of the study was to evaluate influence of source of data, information flows and exchange platforms on level of HIS feedback in public health facilities Methodology: The paper used a desk study review methodology where relevant empirical literature was reviewed to identify main themes and to extract knowledge gaps. Findings: The study concludes that there was feedback

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25

Wolfe, Karen. "Data Base or Word Processing: Knowing the Difference Can Make the Difference." AAOHN Journal 40, no. 4 (April 1992): 194–95. http://dx.doi.org/10.1177/216507999204000407.

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26

Jackson, Heide, and Edward R. Berchick. "Improvements in Uninsurance Estimates for Fully Imputed Cases in the Current Population Survey Annual Social and Economic Supplement." INQUIRY: The Journal of Health Care Organization, Provision, and Financing 57 (January 2020): 004695802092355. http://dx.doi.org/10.1177/0046958020923554.

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In 2019, the Current Population Survey Annual Social and Economic Supplement introduced updates to data processing, including to the imputation of health insurance for cases with no reported health insurance information. This article examines the impact on health insurance estimates of modernized imputation procedures that were part of a redesign of the Current Population Survey Annual Social and Economic Supplement. We use descriptive analysis and multinomial logistic regression to examine whether imputation biases estimates of health insurance coverage using data from the 2017 Current Popula

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27

Lyons, Ronan A. "How much does quality matter: the value of data." Injury Prevention 26, no. 4 (July 21, 2020): 397–99. http://dx.doi.org/10.1136/injuryprev-2019-043369.

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In a world of competing priorities, accurate production of information on the scale of the injury burden and the effectiveness of prevention-orientated interventions and policies is important; hence, data quality matters. This article surveys the literature about what is known about data quality in the injury field and developments to improve the quality and usability of information, particularly through triangulation of data sources, data linkage and unlocking the potential for more deeply phenotyped data through natural language processing.

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28

Martínez-Castaño, Rodrigo, Juan C. Pichel, and David E. Losada . "A Big Data Platform for Real Time Analysis of Signs of Depression in Social Media." International Journal of Environmental Research and Public Health 17, no. 13 (July 1, 2020): 4752. http://dx.doi.org/10.3390/ijerph17134752.

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In this paper we propose a scalable platform for real-time processing of Social Media data. The platform ingests huge amounts of contents, such as Social Media posts or comments, and can support Public Health surveillance tasks. The processing and analytical needs of multiple screening tasks can easily be handled by incorporating user-defined execution graphs. The design is modular and supports different processing elements, such as crawlers to extract relevant contents or classifiers to categorise Social Media. We describe here an implementation of a use case built on the platform that monito

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29

Salsburg, David. "Deming Principles Applied to Processing Data from Case Report Forms." Drug Information Journal 36, no. 1 (January 2002): 135–41. http://dx.doi.org/10.1177/009286150203600117.

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30

Black, Dennis, Kjeld Molvig, Anna Bagniewska, Stan Edlavitch, Cary Fox, Stephen Hulley, and W. McFate Smith. "A Distributed Data Processing System for a Multicenter Clinical Trial." Drug Information Journal 20, no. 1 (January 1986): 83–92. http://dx.doi.org/10.1177/009286158602000113.

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31

Alwitt, Josh, and John Kinney. "The Impact of Document Image Management on Clinical Data Processing." Drug Information Journal 27, no. 4 (October 1993): 995–1000. http://dx.doi.org/10.1177/009286159302700409.

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32

English, Ned, Andrew Anesetti-Rothermel, Chang Zhao, Andrew Latterner, Adam F. Benson, Peter Herman, Sherry Emery, et al. "Image Processing for Public Health Surveillance of Tobacco Point-of-Sale Advertising: Machine Learning–Based Methodology." Journal of Medical Internet Research 23, no. 8 (August 27, 2021): e24408. http://dx.doi.org/10.2196/24408.

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Background With a rapidly evolving tobacco retail environment, it is increasingly necessary to understand the point-of-sale (POS) advertising environment as part of tobacco surveillance and control. Advances in machine learning and image processing suggest the ability for more efficient and nuanced data capture than previously available. Objective The study aims to use machine learning algorithms to discover the presence of tobacco advertising in photographs of tobacco POS advertising and their location in the photograph. Methods We first collected images of the interiors of tobacco retailers

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33

Budhiningtias Winanti, Marliana, and Meylan Lesnusa. "Sistem Informasi Pelayanan Data Pasien pada Laboratorium UPTD Balai Kesehatan Paru Masyarakat (BKPM) Provinsi Maluka." Jurnal Manajemen Informatika (JAMIKA) 9, no. 1 (May 13, 2019): 1–8. http://dx.doi.org/10.34010/jamika.v9i1.1533.

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The development of globalization brings with significant impact for every layer of society, especially the development of many technologies needed by every human being, not least in the areas of employment such as health, and others. In this case the Public Lung Health Center (BKPM) Maluku province is the center of the health inspection service laboratory. Where every day a lot of people who come from different places to check their condition to obtain the required health outcomes, but the increase in performance of health services is still not properly fit most people's expectations, because

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34

Chorianopoulos, Konstantinos, and Karolos Talvis. "Flutrack.org: Open-source and linked data for epidemiology." Health Informatics Journal 22, no. 4 (July 26, 2016): 962–74. http://dx.doi.org/10.1177/1460458215599822.

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Epidemiology has made advances, thanks to the availability of real-time surveillance data and by leveraging the geographic analysis of incidents. There are many health information systems that visualize the symptoms of influenza-like illness on a digital map, which is suitable for end-users, but it does not afford further processing and analysis. Existing systems have emphasized the collection, analysis, and visualization of surveillance data, but they have neglected a modular and interoperable design that integrates high-resolution geo-location with real-time data. As a remedy, we have built

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35

Bhat, Mohammad Hanan. "A Comprehensive Multi-Modal Framework for Plant Health Monitoring." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 20, 2021): 1793–95. http://dx.doi.org/10.22214/ijraset.2021.36739.

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: Plant health monitoring has been a significant field of research since a very long time. The scope of this research work conducted lies in the vast domain of plant pathology with its applications extending in the field of agriculture production monitoring to forest health monitoring. It deals with the data collection techniques based on IOT, pre-processing and post-processing of Image dataset and identification of disease using deep learning model. Therefore, providing a multi-modal end-to-end approach for plant health monitoring. This paper reviews the various methods used for monitoring pl

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36

Kassekert, R., M. Easwar, M. Glaser, R. Ventham, and A. Bate. "PNS271 Automation in Routine Use for Data Collection and Processing for Scalable Faster RWE Generation." Value in Health 23 (December 2020): S686. http://dx.doi.org/10.1016/j.jval.2020.08.1715.

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Blumenthal, Wendy, Temitope O. Alimi, Sandra F. Jones, David E. Jones, Joseph D. Rogers, Vicki B. Benard, and Lisa C. Richardson. "Using informatics to improve cancer surveillance." Journal of the American Medical Informatics Association 27, no. 9 (September 1, 2020): 1488–95. http://dx.doi.org/10.1093/jamia/ocaa149.

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Abstract Objectives This review summarizes past and current informatics activities at the Centers for Disease Control and Prevention National Program of Cancer Registries to inform readers about efforts to improve, standardize, and automate reporting to public health cancer registries. Target audience The target audience includes cancer registry experts, informaticians, public health professionals, database specialists, computer scientists, programmers, and system developers who are interested in methods to improve public health surveillance through informatics approaches. Scope This review pr

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38

Buchan, I., and J. Ainsworth. "Combining Health Data Uses to Ignite Health System Learning." Methods of Information in Medicine 54, no. 06 (2015): 479–87. http://dx.doi.org/10.3414/me15-01-0064.

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SummaryObjectives: In this paper we aim to characterise the critical mass of linked data, methods and expertise required for health systems to adapt to the needs of the populations they serve – more recently known as learning health systems. The objectives are to: 1) identify opportunities to combine separate uses of common data sources in order to reduce duplication of data processing and improve information quality; 2) identify challenges in scaling-up the reuse of health data sufficiently to support health system learning.Methods: The challenges and opportunities were identified through a s

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Lys, Candice, Dionne Gesink, Carol Strike, and June Larkin. "Body Mapping as a Youth Sexual Health Intervention and Data Collection Tool." Qualitative Health Research 28, no. 7 (January 5, 2018): 1185–98. http://dx.doi.org/10.1177/1049732317750862.

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In this article, we describe and evaluate body mapping as (a) an arts-based activity within Fostering Open eXpression Among Youth (FOXY), an educational intervention targeting Northwest Territories (NWT) youth, and (b) a research data collection tool. Data included individual interviews with 41 female participants (aged 13–17 years) who attended FOXY body mapping workshops in six communities in 2013, field notes taken by the researcher during the workshops and interviews, and written reflections from seven FOXY facilitators on the body mapping process (from 2013 to 2016). Thematic analysis exp

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40

Martin-Sanchez, F., and V. Maojo. "Bioinformatics: Towards New Directions for Public Health." Methods of Information in Medicine 43, no. 03 (2004): 208–14. http://dx.doi.org/10.1055/s-0038-1633861.

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Summary Objectives: Epidemiologists are reformulating their classical approaches to diseases by considering various issues associated to “omics” areas and technologies. Traditional differences between epidemiology and genetics include background, training, terminologies, study designs and others. Public health and epidemiology are increasingly looking forward to using methodologies and informatics tools, facilitated by the Bioinformatics community, for managing genomic information. Our aim is to describe which are the most important implications related with the increasing use of genomic infor

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Perpoil, Antoine, Gael Grimandi, Stéphane Birklé, Jean-François Simonet, Anne Chiffoleau, and François Bocquet. "Public Health Impact of Using Biosimilars, Is Automated Follow up Relevant?" International Journal of Environmental Research and Public Health 18, no. 1 (December 29, 2020): 186. http://dx.doi.org/10.3390/ijerph18010186.

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Biologic reference drugs and their copies, biosimilars, have a complex structure. Biosimilars need to demonstrate their biosimilarity during development but unpredictable variations can remain, such as micro-heterogeneity. The healthcare community may raise questions regarding the clinical outcomes induced by this micro-heterogeneity. Indeed, unwanted immune reactions may be induced for numerous reasons, including product variations. However, it is challenging to assess these unwanted immune reactions because of the multiplicity of causes and potential delays before any reaction. Moreover, saf

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Pynzaru, Iury V. "HEALTH ASSESSMENT OF WORKERS OF MEAT PROCESSING PLANTS." Hygiene and sanitation 98, no. 3 (April 29, 2019): 280–87. http://dx.doi.org/10.18821/0016-9900-2019-98-3-280-287.

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Health assessment of workers of four meat processing plants in the Republic of Moldova in the 2011-2015 was carried out. The analysis of temporary disability showed the incidence the respiratory diseases (13.9±1.3 cases for 134.0±17.1 days per 100 workers) to prevail in the structure of disability), followed by the diseases of circulatory system (5.90±0.52 cases and 85.0±9.0 days per 100 workers) as well as the diseases of bone and muscular system (3.54±0.67 cases and 55.2±12.9 days per 100 workers), and diseases of digestive system (3.11±0.44 cases and 45.9±6.2 days of 100 workers) and injuri

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Mchenry, Daniel James, and Nigel Mckelvey. "The Ethical Issues Surrounding Sections 175-178 of the UK's Data Protection Bill." International Journal of Innovation in the Digital Economy 10, no. 1 (January 2019): 53–60. http://dx.doi.org/10.4018/ijide.2019010105.

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There is growing concern that a new data ethics regime that has been introduced into the current draft of the data protection bill may be ethically problematic. The changes are designed to be a framework for data processing but health data privacy advocacy group medconfidential has voiced their concerns at the development. The provider has claimed that the government is trying to push through the regime without first giving the public a chance to engage in discussions about how public-sector data should be stored and processed. This article will discuss ethical issues surrounding the proposed

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Geukes, Cornelia, and Horst M. Müller. "Physiological Correlates of Processing Health-Related Information: An Idea for the Adoption of a Foreign Field." Nursing Reports 11, no. 1 (March 17, 2021): 175–86. http://dx.doi.org/10.3390/nursrep11010017.

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Measuring health may refer to the measurement of general health status through measures of physical function, pain, social health, psychological aspects, and specific disease. Almost no evidence is available on the possible interaction of physiological measures and correlating emotional–affective states that are triggered by dealing with individual health-relevant issues and their specific processing modes. Public health research has long been concerned with the processing of health-related information. However, it is not yet clear which factors influence access and the handling of health-rela

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Liu, Jingjing, Guangyuan Shi, Jing Zhou, and Qiumei Yao. "Prediction of College Students’ Psychological Crisis Based on Data Mining." Mobile Information Systems 2021 (May 17, 2021): 1–7. http://dx.doi.org/10.1155/2021/9979770.

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The development of a college students’ psychological management system has become an essential indicator to monitor and prevent the psychological crisis. University student management databases accumulate massive data, but the conventional data processing tasks are restricted to simple statistical analysis, storage, and query management. This paper discusses the application of big data technology for the current psychological management system by investigating psychological crisis screening indicators. Data mining techniques are used to realize the dynamic management of psychological early war

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Brown, Adrian Paul, and Sean M. Randall. "Secure Record Linkage of Large Health Data Sets: Evaluation of a Hybrid Cloud Model." JMIR Medical Informatics 8, no. 9 (September 23, 2020): e18920. http://dx.doi.org/10.2196/18920.

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Background The linking of administrative data across agencies provides the capability to investigate many health and social issues with the potential to deliver significant public benefit. Despite its advantages, the use of cloud computing resources for linkage purposes is scarce, with the storage of identifiable information on cloud infrastructure assessed as high risk by data custodians. Objective This study aims to present a model for record linkage that utilizes cloud computing capabilities while assuring custodians that identifiable data sets remain secure and local. Methods A new hybrid

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Botes, Marietjie, Melodie Nöthling Slabbert, and Antonel Olckers. "Data Commercialisation in the South African Health Care Context." Potchefstroom Electronic Law Journal 24 (August 12, 2021): 1–35. http://dx.doi.org/10.17159/1727-3781/2021/v24i0a8577.

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Realisation of the value and the commercialisation potential of data is gaining exponential momentum. The combination of historical data exploitations and the use of technologies that allow for the triangulation of data results in the collection, storage, and processing of massive amounts of data require diligent data management, including adherence to privacy and other laws, both nationally and internationally. The intrinsic value of scientific data, especially in genomics, becomes apparent when data are shared, often in collaboration with international partners, and compiled into big data se

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Lach, Daniel Eryk. "Przetwarzanie i ochrona danych dotyczących zdrowia przez organizatora systemu opieki zdrowotnej." Studia Prawa Publicznego, no. 3 (31) (October 15, 2020): 53–72. http://dx.doi.org/10.14746/spp.2020.3.31.3.

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The protection of individuals regarding to the processing of personal data is one of the fundamental rights. The General Data Protection Regulation (GDPR) lays down rules relating to the protection of natural persons with regard to the processing of personal data and rules relating to the free movement of personal data. Data concerning health is one of the areas the GDPR defines as special personal data, the so-called sensitive data. With regard to these data, the GDPR allows their processing only on an exceptional basis, in certain situations. According to Art. 6 sec. 1 let. e GDPR and art. 9

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Sheikh, Asim. "The Data Protection (Amendment) Act, 2003: The Data Protection Directive and its Implications for Medical Research in Ireland." European Journal of Health Law 12, no. 4 (2005): 357–72. http://dx.doi.org/10.1163/157180905775088568.

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AbstractDirective 95/46/EC on the Protection of Individuals with regard to the Processing of Personal Data and on the Free Movement of Such Data has been transposed into national law and is now the Data Protection (Amendment) Act, 2003.The Directive and the transposing Act provide for new obligations to those processing data. The new obligation of primary concern is the necessity to obtain consent prior to the processing of data (Article 7, Directive 95/46/EC). This has caused much concern especially in relation to 'secondary data' or 'archived data'.There exist, what seem to be in the minds o

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Sujin, J. S., N. Gandhiraj, D. Selvakumar, and Satheesh S. Kumar. "Public E-Health Network System Using Arduino Controller." Journal of Computational and Theoretical Nanoscience 16, no. 2 (February 1, 2019): 544–49. http://dx.doi.org/10.1166/jctn.2019.7766.

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An E-health Multifunctional system is proposed for people in all age category in this work. Simply, the different sensors are fixed on a coat. When the coatis worn by people, the sensors situated in the coat will be get activated. Then it will automatically examine various parameters about health and the same information send to monitor or website or mobile. This is used for personal and social use. An example is presented with different sensor signals and continuous Real time monitoring the health changes from the home. Sensors are embedded in to the atmosphere, it will give various changes w

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