Relevant bibliographies by topics / Personalized prediction / Dissertations / Theses
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Dissertations / Theses on the topic 'Personalized prediction'

Author: Grafiati
Published: 1 June 2024
Last updated: 31 July 2025

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1

Fernando, Warnakulasuriya Chandima. "Blood Glucose Prediction Models for Personalized Diabetes Management." Thesis, North Dakota State University, 2018. https://hdl.handle.net/10365/28179.

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Effective blood glucose (BG) control is essential for patients with diabetes. This calls for an immediate need to closely keep track of patients' BG level all the time. However, sometimes individual patients may not be able to monitor their BG level regularly due to all kinds of real-life interference. To address this issue, in this paper we propose machine-learning based prediction models that can automatically predict patients BG level based on their historical data and known current status. We take two approaches, one for predicting BG level only using individual's data and second is to use
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Shen, Yuanyuan. "Ordinal Outcome Prediction and Treatment Selection in Personalized Medicine." Thesis, Harvard University, 2015. http://nrs.harvard.edu/urn-3:HUL.InstRepos:17463982.

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In personalized medicine, two important tasks are predicting disease risk and selecting appropriate treatments for individuals based on their baseline information. The dissertation focuses on providing improved risk prediction for ordinal outcome data and proposing score-based test to identify informative markers for treatment selection. In Chapter 1, we take up the first problem and propose a disease risk prediction model for ordinal outcomes. Traditional ordinal outcome models leave out intermediate models which may lead to suboptimal prediction performance; they also don't allow for non-lin
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Reggiani, Francesco. "Development and assessment of bioinformatics methods for personalized medicine." Doctoral thesis, Università degli studi di Padova, 2019. http://hdl.handle.net/11577/3424693.

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The human genome is a source of information for researchers that study complex diseases with the perspective of a better understanding of the pathologies and the development of new therapeutic strategies. Starting from the beginning of the current century, a growing number of technologies devoted to DNA sequencing have emerged, generally referred to as Next Generation Sequencing (NGS) technologies. NGS gradually decreased the cost of sequencing a human genome to around US$1000, enabling the use of these technologies for clinical and research purposes, such as Genome-wide association studies (G
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Bucci, Francesca. "Personalized biomechanical model of a patient with severe hip osteoarthritis for the prediction of pelvic biomechanics." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018. http://amslaurea.unibo.it/15879/.

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L’articolazione dell'anca è un'articolazione sinoviale sferica che costituisce la connessione primaria tra gli arti inferiori e lo scheletro della parte superiore del corpo. Durante le attività quotidiane di routine, carichi anormali ripetuti sull'anca possono portare alla danneggiamento della cartilagine articolare e conseguentemente , all’osteoartrite (OA). L'OA dell'anca è una condizione muscolo-scheletrica cronica e progressiva, il cui trattamento per i pazienti severi è l'artroplastica totale dell'anca (THA). Il centro dell'articolazione dell'anca (HJC) ha grande importanza nell’analisi
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Youssfi, Younès. "Exploring Risk Factors and Prediction Models for Sudden Cardiac Death with Machine Learning." Electronic Thesis or Diss., Institut polytechnique de Paris, 2023. http://www.theses.fr/2023IPPAG006.

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La mort subite de l'adulte est définie comme une mort inattendue sans cause extracardiaque évidente, survenant avec un effondrement rapide en présence d'un témoin, ou en l'absence de témoin dans l'heure après le début des symptômes. Son incidence est estimée à 350,000 personnes par an en Europe et 300,000 personnes aux Etats-Unis, ce qui représente 10 à 20% des décès dans les pays industrialisés. Malgré les progrès réalisés dans la prise en charge, le pronostic demeure extrêmement sombre. Moins de 10% des patients sortent vivants de l'hôpital après la survenue d'une mort subite. Les défibrilla
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Bellón, Molina Víctor. "Prédiction personalisée des effets secondaires indésirables de médicaments." Thesis, Paris Sciences et Lettres (ComUE), 2017. http://www.theses.fr/2017PSLEM023/document.

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Les effets indésirables médicamenteux (EIM) ont des répercussions considérables tant sur la santé que sur l'économie. De 1,9% à 2,3% des patients hospitalisés en sont victimes, et leur coût a récemment été estimé aux alentours de 400 millions d'euros pour la seule Allemagne. De plus, les EIM sont fréquemment la cause du retrait d'un médicament du marché, conduisant à des pertes pour l'industrie pharmaceutique se chiffrant parfois en millions d'euros.De multiples études suggèrent que des facteurs génétiques jouent un rôle non négligeable dans la réponse des patients à leur traitement. Cette rép
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Wood, Dawn Helaine. "Personality representation : predicting behaviour for personalised learning support." Thesis, University of Hull, 2010. http://hydra.hull.ac.uk/resources/hull:6862.

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The need for personalised support systems comes from the growing number of students that are being supported within institutions with shrinking resources. Over the last decade the use of computers and the Internet within education has become more predominant. This opens up a range of possibilities in regard to spreading that resource further and more effectively. Previous attempts to create automated systems such as intelligent tutoring systems and learning companions have been criticised for being pedagogically ineffective and relying on large knowledge sources which restrict their domain of
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8

Levillain, Hugo. "Prediction and improvement of radioembolization outcome using personalised treatment and dosimetry." Doctoral thesis, Universite Libre de Bruxelles, 2021. https://dipot.ulb.ac.be/dspace/bitstream/2013/320561/3/PhDTM.docx.

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Radioembolization (also called selective internal radiation therapy, SIRT) with yttrium-90 (90Y)-loaded microspheres has been broadly adopted as a locoregional therapy for primary and metastatic liver cancers. Although radioembolization is a well-established therapy, efforts to personalise and refine the planning and administration of therapy are ongoing. The ability to accurately predict, plan and deliver optimal doses to tumour and non-tumour tissues, including final validation of dose distribution, is essential for successful radiotherapy. Determining the true dose absorbed by tissue compar
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9

Tay, Darwin. "Decision support continuum paradigm for cardiovascular disease : towards personalized predictive models." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/25032.

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Clinical decision making is a ubiquitous and frequent task physicians make in their daily clinical practice. Conventionally, physicians adopt a cognitive predictive modelling process (i.e. knowledge and experience learnt from past lecture, research, literature, patients, etc.) for anticipating or ascertaining clinical problems based on clinical risk factors that they deemed to be most salient. However, with the inundation of health data and the confounding characteristics of diseases, more effective clinical prediction approaches are required to address these challenges. Approximately a few ce
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10

Mohammed, Rafiq. "Personalized call center traffic prediction to enhance management solution with reference to call traffic jam mitigation a case study on Telecom New Zealand Ltd. : a dissertation submitted to Auckland University of Technology in partial fulfillment of the requirements for the degree of Master of Computer and Information Sciences (MCIS), 2008 /." Click here to access this resource online, 2008. http://hdl.handle.net/10292/479.

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11

Cheng, Chih-Wen. "Development of integrated informatics analytics for improved evidence-based, personalized, and predictive health." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54872.

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Advanced information technologies promise a massive influx of individual-specific medical data. These rich sources offer great potential for an increased understanding of disease mechanisms and for providing evidence-based and personalized clinical decision support. However, the size, complexity, and biases of the data pose new challenges, which make it difficult to transform the data to useful and actionable knowledge using conventional statistical analysis. The so-called “Big Data” era has created an emerging and urgent need for scalable, computer-based data mining methods that can turn data
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12

Alderdice, Matthew. "Personalised medicine in rectal cancer : understanding and predicting response to neoadjuvant chemoradiotherapy." Thesis, Queen's University Belfast, 2017. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.725327.

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Around 12-15% of patients with locally advanced rectal cancer (LARC) undergo a pathologically complete response (Tumour Regression Grade 4 - TRG4) to neoadjuvant chemoradiotherapy; the remainder exhibit a spectrum of tumour regression (TRG1-3). Understanding therapy-related genomic alterations may help us better predict response, progression-free and overall survival, and also identify both novel and repurposed treatment strategies based on the underlying biology of the disease. The Northern Ireland Biobank provided 48 formalin fixed paraffin embedded (FFPE) rectal cancer biopsies and matched
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Gilholm, Patricia. "Methods for personalised predictive modelling of developmental milestones for children with disabilities." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/212038/1/Patricia%20Gilholm%20Thesis.pdf.

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This thesis developed methods for personalised modelling of developmental milestones for children with disabilities. Using data containing 348 milestone measurements from a small sample of children with a diverse range of disabilities, methods were developed to create a comprehensive personalised developmental profile for each child. These profiles incorporate multiple developmental domains and are designed to be updated in real time so that parents can be provided with feedback as their child develops. The outputs of the methods developed in this thesis will be used to help inform decision-ma
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Park, Keon-Young. "Predicting patient-to-patient variability in proteolytic activity and breast cancer progression." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/53479.

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About one in eight women in the United States will develop breast cancer over the course of her lifetime. Moreover, patient-to-patient variability in disease progression continues to complicate clinical decisions in diagnosis and treatment for breast cancer patients. Early detection of tumors is a key factor influencing patient survival, and advancements in diagnostic and imaging techniques has allowed clinicians to spot smaller sized lesions. There has also been an increase in premature treatments of non-malignant lesions because there is no clear way to predict whether these lesions will bec
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15

Fu, Yu. "Analyse intégrative de données génomiques et pharmacologiques pour une meilleure prédiction de la réponse aux médicaments anti-cancer." Thesis, Université Paris-Saclay (ComUE), 2016. http://www.theses.fr/2016SACLS560.

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Analyse intégrative de données génomiques et pharmacologiques pour améliorer la prédiction de la réponse aux thérapies cibléesL'utilisation de thérapies ciblées dans le contexte de la médecine personnalisée du cancer a permis d’améliorer le traitement des patients dans différents types de cancer. Cependant, alors que la décision thérapeutique est basée sur une unique altération moléculaire (par exemple une mutation ou un changement du nombre de copies d’un gène), les tumeurs montrent différents degrés de réponse. Dans cette thèse, nous démontrons que la décision thérapeutique basée sur une uni
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Hwang, Yuan-Chun. "Local and personalised models for prediction, classification and knowledge discovery on real world data modelling problems." Click here to access this resource online, 2009. http://hdl.handle.net/10292/776.

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This thesis presents several novel methods to address some of the real world data modelling issues through the use of local and individualised modelling approaches. A set of real world data modelling issues such as modelling evolving processes, defining unique problem subspaces, identifying and dealing with noise, outliers, missing values, imbalanced data and irrelevant features, are reviewed and their impact on the models are analysed. The thesis has made nine major contributions to information science, includes four generic modelling methods, three real world application systems that apply t
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Bragazzi, Nicola Luigi [Verfasser], and Norbert [Akademischer Betreuer] Hampp. "Nanogenomics and Nanoproteomics Enabling Personalized, Predictive and Preventive Medicine / Nicola Luigi Bragazzi. Betreuer: Norbert Hampp." Marburg : Philipps-Universität Marburg, 2014. http://d-nb.info/1051935334/34.

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Cissoko, Mamadou Ben Hamidou. "Adaptive time-aware LSTM for predicting and interpreting ICU patient trajectories from irregular data." Electronic Thesis or Diss., Strasbourg, 2024. http://www.theses.fr/2024STRAD012.

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En médecine prédictive personnalisée, modéliser avec précision la maladie et les processus de soins d'un patient est crucial en raison des dépendances temporelles à long terme inhérentes. Cependant, les dossiers de santé électroniques (DSE) se composent souvent de données épisodiques et irrégulières, issues des admissions hospitalières sporadiques, créant des schémas uniques pour chaque séjour hospitalier.Par conséquent, la construction d'un modèle prédictif personnalisé nécessite une considération attentive de ces facteurs pour capturer avec précision le parcours de santé du patient et aider
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IANZA, ANNA. "VALIDATION OF PREDICTIVE AND PROGNOSTIC BIOMARKERS AS A GUIDE FOR A PERSONALIZED APPROACH IN SOLID TUMOURS." Doctoral thesis, Università degli Studi di Trieste, 2020. http://hdl.handle.net/11368/2973745.

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Breast cancer (BC), Colorectal Cancer (CRC) and Non-Small Cell Lung Cancer (NSCLC) are among the most commonly diagnosed solid tumors, and occupy the first places in the mortality rankings. Compared to an old fashioned one-size-fits-all approach, precision medicine offers the possibility to accurately choose the most appropriate therapeutic strategy, that fits the patients not only from the clinical (age, comorbidities) but also from a molecular point of view. A genetic and biological understanding of the tumor, integrated with a weighted analysis of results can help the clinician in designing
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Tsur, Neta [Verfasser], and Markus [Akademischer Betreuer] Morrison. "Predicting response to immunotherapy in metastatic melanoma by a personalized mathematical model / Neta Tsur ; Betreuer: Markus Morrison." Stuttgart : Universitätsbibliothek der Universität Stuttgart, 2020. http://d-nb.info/1215574142/34.

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21

Biasci, Daniele. "Predicting prognosis in Crohn's disease." Thesis, University of Cambridge, 2017. https://www.repository.cam.ac.uk/handle/1810/270034.

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22

Gil, Ortega Joan. "Improved and efficient therapy of acromegaly by implementation of a personalized and predictive algorithm including molecular and clinical information." Doctoral thesis, Universitat Autònoma de Barcelona, 2020. http://hdl.handle.net/10803/671121.

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El tractament farmacològic actual de l’acromegàlia està basat en el mètode de prova i error. En aquesta malaltia, un control bioquímic ràpid és decisiu per evitar comorbiditats i reduir la mortalitat. Afortunadament, avui en dia tenim diversos tractaments farmacològics amb els lligands del receptor de la somatostatina (LRS) de primera generació com a primera línia farmacològica. Tanmateix més del 50% dels pacients no aconsegueixen controlar els nivells hormonals amb els LRS la qual cosa pot arribar a endarrerir el control bioquímic de la malaltia durant mesos o fins i tot més d’un any. El prin
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Ahmadi, Matthew. "Application of machine learning approaches for activity recognition and energy expenditure prediction in free living children and adolescents." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/206178/1/Matthew%20Nguyen_Ahmadi_Thesis.pdf.

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This thesis was the first to comprehensively evaluate the application of machine learning approaches for physical activity assessment under real world conditions among children with unique movement patterns. This included preschool age children and children with cerebral palsy. Collectively, the findings from this thesis conclude activity classification models trained on laboratory-based data fail to generalise to a real-world environment and models trained on free-living data have superior accuracy. In contrast, energy expenditure prediction models trained on laboratory-based data generalise
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Salehe, Bajuna Rashid. "Predictive tools for the study of variations in ADP platelet responses : implications for personalised CVD risk and prevention strategies." Thesis, University of Reading, 2017. http://centaur.reading.ac.uk/74255/.

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The major aim of this project is to develop novel computational approaches for rapid identification of key omic variations, particularly SNPs that are likely to be associated with the variability of the ADP (Adenosine diphosphate) activated platelet responses. The ADP platelet response was chosen as a model system due to its distinct role during the platelet amplification and aggregation, and it is the main therapeutic target for cardiovascular disease (CVD) antiplatelet drug treatments. Based on recent studies, CVD is currently the second lethal noncommunicable disease after cancer in both de
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Alyamani, Nayef A. "The impact of cancer physicians' and patients' attitudes on personalised prescription of novel targeted anticancer drugs using predictive biomarkers." Thesis, University of Aberdeen, 2014. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=211204.

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Background: The use of novel targeted anticancer drugs in clinical practice is rapidly increasing. As the use of these drugs increases, so does the need to develop biomarkers to optimise the drugs' clinical and cost effectiveness. The attitudes and views of all stakeholders regarding the optimal use of predictive biomarkers in guiding personalised medicine are crucial for identifying acceptable criteria of predictive biomarker tests to guide future biomarker development. To gain insight into these views, we aimed to develop and validate a survey tool that would aid in assessing attitudes of ca
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Wang, Hao. "Screening multi-omics biomarkers for suboptimal health status." Thesis, Edith Cowan University, Research Online, Perth, Western Australia, 2021. https://ro.ecu.edu.au/theses/2431.

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Background Suboptimal health status (SHS) is an intermediate health status between ideal health and diseases. It is characterized by chronic fatigue, perception of health complaints and a cluster of physical symptoms lasting for more than three months. SHS is recognised as a subclinical, reversible stage of chronic diseases. Objectives Study I. To investigate the prevalence of SHS in a cross-sectional study. Study II. To screen transcriptomic biomarkers for SHS in a case-control study. Study III. To screen metabolomics biomarkers for SHS in a case-control study. Materials and Methods Study
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Kim, Jin Hee. "Functional genomics of cardiovascular disease risk." Thesis, Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/51769.

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Understanding variability of heath status is highly likely to be an important component of personalized medicine to predict health status of individuals and to promote personal health. Evidences of Genome Wide Association Study and gene expression study indicating that genetic factors affect the risk susceptibility of individuals have suggested adding genetic factors as a component of health status measurements. In order to validate or to predict health risk status with collected personal data such as clinical measurements or genomic data, it is important to have a well-established profile of
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Hoogendoorn, Corné. "A statistical dynamic cardiac atlas for the virtual physiological human: construction and application." Doctoral thesis, Universitat Pompeu Fabra, 2014. http://hdl.handle.net/10803/132632.

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This thesis is centered on the construction of a cardiac atlas to serve as a common reference frame in the Virtual Physiological Human (VPH). The construction covers the entire construction pipeline, starting from a set of 3D+t multislice computed tomography images, then performing a spatial normalization of these images, segmentation of the synthesized mean image, multi-structure meshing, and finally mapping of the mesh back to the population of images. In addition, two applications are presented in this thesis. First, the atlas is used to frame a spatio-temporal model of cardiac morphology
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Oltra-Cucarella, Javier. "Revisión de los criterios diagnósticos del deterioro cognitivo leve: nuevos marcadores predictivos de la enfermedad de Alzheimer." Doctoral thesis, Universidad de Alicante, 2018. http://hdl.handle.net/10045/103153.

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La presente tesis doctoral se centra en la investigación sobre los criterios diagnósticos del Deterioro Cognitivo Leve y el análisis de nuevos marcadores predictivos de la Enfermedad de Alzheimer. Este trabajo consta de diez capítulos articulados en los siguientes apartados: a) introducción y objetivos, b) estudios empíricos publicados, c) estudios empíricos en revisión, d) discusión general, limitaciones, implicaciones clínicas y perspectivas de futuro, y e) conclusiones. Los estudios empíricos que conforman esta tesis doctoral se han centrado en dos colectivos de interés: personas con Deteri
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Gallart, Masià Salvador. "Predicción de los trastornos de la personalidad del Eje II del DSM-IV-TR a partir de diferentes modelos dimensionales: Costa y McCrae, Zuckerman y Cloninger." Doctoral thesis, Universitat de Lleida, 2015. http://hdl.handle.net/10803/306603.

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Aquest estudi pretén comprovar l’existència o no de diferències estructurals entre la personalitat normal i patològica. D’altra banda, interessa veure la capacitat predictiva dels tests de personalitat normal respecte als trastorns de la personalitat segons els criteris del DSM-IV-TR, en població sana i clínica. S'utilitzen tres instruments psicomètrics (NEO-PI-R, ZKPQ-50-CC i TCI-R), pertanyents als models dimensionals de personalitat de Costa i McCrae (Cinc Grans Factors), Zuckerman (Cinc Alternatius) i Cloninger (Psicobiològic de Temperament i Caràcter), respectivament. Els resultats confir
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Alcenat, Stéphane. "Assurance maladie et tests génétiques." Thesis, Bourgogne Franche-Comté, 2020. http://www.theses.fr/2020UBFCB002.

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Cette thèse apporte trois contributions majeures. Le premier chapitre, un article paru dans la Revue Française d’Économie n°2/vol XXXIV, propose une revue de la littérature sur les implications de la régulation des tests génétiques de prédisposition sur le marché de l'assurance santé. Nous montrons que les formes actuelles de régulation réalisent un arbitrage entre la maximisation du bien-être social ex ante et l’incitation à la prévention. Cet arbitrage est conditionné par la façon dont l’acquisition de l’information affecte les comportements de prévention et de révélation des agents, la disc
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Cornec-Le, Gall Emilie. "Polykystose rénale autosomique dominante : de la génétique moléculaire au développement d'outils pronostiques." Thesis, Brest, 2015. http://www.theses.fr/2015BRES0030.

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La Polykystose Rénale Autosomique Dominante (PKRAD) est une des pathologies héréditaires les plus fréquentes et affecte environ un individu sur 1000. Elle se caractérise par une importante variabilité clinique, notamment dans l’âge de survenue de l’insuffisance rénale terminale. Deux gènes sont en cause : le gène PKD1 situé sur le chromosome 16 (85% des cas) et le gène PKD2 situé sur le chromosome 4 (15% des cas). Les progrès majeurs dans la compréhension des mécanismes moléculaires impliqués ont permis le développement de stratégies thérapeutiques spécifiques, et de nouvelles questions surgis
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Fritz, Justine. "Validation préclinique d'un test de prédiction d'efficacité de médicaments anti-cancéreux : application au glioblastome, cancer colorectal et cancer de la prostate." Thesis, Strasbourg, 2016. http://www.theses.fr/2016STRAJ058.

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Nous avons développé un nouveau test de prédiction de l’efficacité de thérapies anti-cancéreuses. Ce concept se base sur la détermination d’une signature moléculaire tumorale par RT-qPCR. Cette signature est issue d’un algorithme de normalisation innovant de comparaison des données d’expression relative des cibles de la tumeur avec celles de tissus de référence. Cette normalisation offre à chaque cible de la signature un rang et un score spécifique permettant de hiérarchiser les voies pro-tumorales afin de trouver la ou les cibles dominantes responsables du développement de la tumeur. La signa
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Prague, Mélanie. "Utilisation des modèles dynamiques pour l'optimisation des traitements des patients infectés par le VIH." Thesis, Bordeaux 2, 2013. http://www.theses.fr/2013BOR22056.

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La plupart des patients infectés par le VIH ont une charge virale qui peut être rendue indétectable par des combinaisons antirétrovirales hautement actives (cART); cependant, il existe des effets secondaires aux traitements. L'utilisation des modèles mécanistes dynamiques basés sur des équations différentielles ordinaires (ODE) a considérablement amélioré les connaissances de la dynamique HIV-système immunitaire et permet d'envisager une personnalisation du traitement. L'objectif de ces travaux de thèse est d'améliorer les techniques statistiques d'estimation de paramètres dans les modèles méc
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Jiang, Tian. "Personalized Defect Prediction." Thesis, 2013. http://hdl.handle.net/10012/7786.

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Academia and industry expend much effort to predict software defects. Researchers proposed many defect prediction algorithms and metrics. While previous defect prediction techniques often take the author of the code into consideration, none of these techniques build a separate prediction model for each developer. Different developers have different coding styles, commit frequencies, and experience levels, which would result in different defect patterns. When the defects of different developers are combined, such differences are obscured, hurting the prediction performance. This thesis proposes
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Kuan, Mei-Lan, and 官美蘭. "Comprehensive and Personalized Stock Performance Prediction." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/27211154926656315250.

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碩士<br>輔仁大學<br>資訊管理學系<br>87<br>This thesis aims to find new value-added services for traditional stock systems based on neural networks. For example, they are capable of soliciting valuable information related to why the stock prediction is made, and furthermore offer investors personalized stock prediction. That is, we attempt to build a comprehensive and personalized stock prediction system, which can become a personalized financial consultant for investors. There are two major components in this system. The first component is a comprehensive component, which is built on the rule e
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YEH, CHAN-CHANG, and 葉展彰. "Building a Personalized Music Emotion Prediction System." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/87377903598187527173.

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Wang, Wei-Chun, and 王威淳. "Personalized Dynamic Prediction Model for Hepatocellular Carcinoma." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/q555ed.

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碩士<br>國立臺灣大學<br>流行病學與預防醫學研究所<br>105<br>Background The predictive model for the risk of hepatocellular carcinoma (HCC) has been developed in previous studies but such kinds of models are often presented for predicting the mean risk of the underlying population. More importantly, the translation of these predictive models into a personalized prediction model for individual risk of hepatocellular carcinoma (HCC) has increasingly gained attention. The objectives of this thesis are to (1) to build up a predictive model for individual risk prediction for HCC by using a Bayesian clinical reasoning al
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Abedtash, Hamed. "An interoperable electronic medical record-based platform for personalized predictive analytics." Diss., 2017. http://hdl.handle.net/1805/13759.

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Indiana University-Purdue University Indianapolis (IUPUI)<br>Precision medicine refers to the delivering of customized treatment to patients based on their individual characteristics, and aims to reduce adverse events, improve diagnostic methods, and enhance the efficacy of therapies. Among efforts to achieve the goals of precision medicine, researchers have used observational data for developing predictive modeling to best predict health outcomes according to patients’ variables. Although numerous predictive models have been reported in the literature, not all models present high prediction p
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Dai, Wuyang. "Detection and prediction problems with applications in personalized health care." Thesis, 2015. https://hdl.handle.net/2144/15651.

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The United States health-care system is considered to be unsustainable due to its unbearably high cost. Many of the resources are spent on acute conditions rather than aiming at preventing them. Preventive medicine methods, therefore, are viewed as a potential remedy since they can help reduce the occurrence of acute health episodes. The work in this dissertation tackles two distinct problems related to the prevention of acute disease. Specifically, we consider: (1) early detection of incorrect or abnormal postures of the human body and (2) the prediction of hospitalization due to heart relate
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Chang, Hsiao-Pei, and 張筱珮. "Personalized Automatic Quiz Generation Based on Reading Difficulty and Proficiency Level Prediction." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/89732120361526910933.

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碩士<br>國立臺灣大學<br>資訊管理學研究所<br>99<br>A lot of research works have been done in the field of automatic quiz generation, however, almost all those studies generate all possible combination of quizzes and only few research consider difficulties of different quizzes. In this study, not only a quiz‘s difficulty but also the difference between learners and the reading difficulty of a document are taken into consideration. Therefore, we design a personalized automatic quiz generation system based on reading difficulty estimation scheme in a given document and proficiency level prediction for a second la
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Hwang, Susan. "Similarity-principle-based machine learning method for clinical trials and beyond." Thesis, 2020. https://hdl.handle.net/2144/41983.

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The control of type-I error is a focal point for clinical trials. On the other hand, it is also critical to be able to detect a truly efficacious treatment in a clinical trial. With recent success in supervised learning (classification and regression problems), artificial intelligence (AI) and machine learning (ML) can play a vital role in identifying efficacious new treatments. However, the high performance of the AI methods, particularly the deep learning neural networks, requires a much larger dataset than those we commonly see in clinical trials. It is desirable to develop a new ML method
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Kureshi, Nelofar. "Personalized Medicine: Development of a Predictive Computational Model for Personalized Therapeutic Interventions." 2013. http://hdl.handle.net/10222/35383.

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Lung cancer is the leading cause of cancer-related deaths among men and women. Non-Small Cell Lung Cancer (NSCLC) constitutes the most common type of lung cancer and is frequently diagnosed at advanced stages. In the past decade, discovery of Epidermal Growth Factor Receptor (EGFR) mutations have heralded a new paradigm of personalized treatment for NSCLC. Clinical studies have shown that molecular targeted therapies increase survival and improve quality of life in patients. Despite these advances, the realization of personalized therapies for NSCLC faces a number of challenges including the i
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Banjar, Haneen Reda. "Personalized Medicine Support System for Chronic Myeloid Leukemia Patients." Thesis, 2018. http://hdl.handle.net/2440/117837.

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Personalized medicine offers the most effective treatment protocols to the individual Chronic Myeloid Leukemia (CML) patients. Understanding the molecular biology that causes CML assists in providing efficient treatment. After the identification of an activated tyrosine kinase BCR-ABL1 as the causative lesion in CML, the first-generation Tyrosine Kinase inhibitors (TKI) imatinib (Glivec®), were developed to inhibit BCR-ABL1 activity and approved as a treatment for CML. Despite the remarkable increase in the survival rate of CML patients treated with imatinib, some patients discontinued imatini
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WU, PING-HUAN, and 吳秉桓. "The Study of Constructing Personalized Portfolio and Predicting Fund Performance." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/54164118355826776293.

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碩士<br>輔仁大學<br>資訊管理學系<br>96<br>The objective of this study is to find the best performance of funds through the classification techniques of data mining. This study uses classification algorithms to construct prediction models as well as combines technical indices and fund attributes for analysis. A secondary purpose of this study is to help investors finding the personalized portfolio through genetic algorithms of evolutionary computation. The results obtained in this study have indicated that decision tree algorithm has better performance than others in constructing prediction models. The acc
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Guggenheim, J. A., Mojarrad Neema Ghorbani, C. Williams, and D. I. Flitcroft. "Genetic prediction of myopia: prospects and challenges." 2017. http://hdl.handle.net/10454/17506.

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Yes<br>Appeals have been made for eye care professionals to start prescribing anti-myopia therapies as part of their routine management of myopic children. 1–3 These calls are fuelled by two key considerations. Firstly, that interventions to slow myopia progression have shown success in randomized controlled trials (RCTs) 4–7, and secondly, appreciation that the risk of sight-threatening complications rises dose-dependently with the level of myopia. 8,9 Notwithstanding existing gaps in knowledge regarding the efficacy of current treatments (see below), these considerations argue that myopia co
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Cameron, Kellas Ross. "Studies on using data-driven decision support systems to improve personalized medicine processes." Thesis, 2018. https://hdl.handle.net/2144/30452.

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This dissertation looks at how new sources of information should be incorporated into medical decision-making processes to improve patient outcomes and reduce costs. There are three fundamental challenges that must be overcome to effectively use personalized medicine, we need to understand: 1) how best to appropriately designate which patients will receive the greatest value from these processes; 2) how physicians and caregivers interpret additional patient-specific information and how that affects their decision-making processes; and finally, (3) how to account for a patient’s ability to enga
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Bessa, Sílvia da Conceição Neto. "Personalized 3D Breast Cancer Models: from Multimodal Registration to Predictive Shape Modelling." Doctoral thesis, 2021. https://hdl.handle.net/10216/136835.

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Villar, Marta Maria Cabral Menéres Posser. "Machine learning approach for personalized recommendations on online platforms: uniplaces case study." Master's thesis, 2021. http://hdl.handle.net/10362/113411.

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Project Work presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence<br>The goal of this project is to develop a model to personalize the user recommendations of an online marketplace named Uniplaces. This online business offers properties for medium and long-term stays, where landlords can directly rent their place to customers (mainly students). Whenever a student makes a reservation, the booking must be approved by the property owner. The current acceptance rate is 25%. The model is
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Melidis, Andreas. "Personalized marketing campaign for upselling using predictive modeling in the health insurance sector." Master's thesis, 2020. http://hdl.handle.net/10362/99076.

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Internship Report presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics<br>Nowadays, with the oversupply of several different solutions in the private Health Insurance sector and the constantly increasing demand for value for money services from the client’s perspective, it becomes clear that Insurance Companies shouldn’t only strive for excellence but also engage their client base by offering solutions that are more suitable to their needs. This project aims, using the power that predictive models can provide, to predict the existing
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