Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 11 of 11 for “"Disease risk prediction"”.
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Cardiovascular disease risk prediction models: does one-score-fit-all?
Cardiovascular disease (CVD) remains the leading cause of death globally and is a major contributor to the global burden of disability and impaired quality of life. Individuals with existing or prior health conditions, including diabetes, cancer, depression, and severe COVID-19 are particularly at …
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Evaluating and enhancing cardiovascular disease risk prediction with algorithmic fairness
Cardiovascular disease (CVD) is the leading cause of morbidity and mortality worldwide, with risk prediction models in widespread clinical use. Yet much remains unknown about the performance of CVD risk prediction models in specific subgroups, and disparities in predictions can exacerbate health …
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Developing and Updating Cardiovascular Disease Risk Prediction Equations: An Exploration of Key Methodological Questions
… about developing and updating cardiovascular disease (CVD) risk prediction equations for people without prior CVD. Methods: Using Health Contact Cohorts (HCCs) constructed by linking national administrative health databases, this thesis comprised four studies: i) an update of policy equations; …
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Disease population genetic simulation framework: towards application in modelling disease risk prediction and heritability rate
… data analysis. Our understanding of genetic disease underpinnings has exploded. It is thus unfortunate that a substantial proportion of these studies continue to be of European populations, while GWAS in Africans and other diverse populations lag behind. Concerns about the disparity in …
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Improving Clinical Risk Models through Integration of Polygenic Risk Scores and Omics
… of loci associated with complex traits and diseases, leading to breakthroughs in human genetics research. However, interpretation of these results is often difficult as the GWAS-identified variants (single-nucleotide polymorphisms [SNPs]) often have small effect estimates on target traits, …
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Risk prediction with genomic data
… various machine learning algorithms to predict disease risk. This thesis investigates this widely used approach of GWAS using Single Nucleotide Polymorphism (SNP) genotype data and a novel approach of disease risk prediction with whole exome sequencing data, namely Whole Exome Wide Association …
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Privacy preserving framework for federated learning in genomics
… of the framework using Type 2 Diabetes disease risk prediction as a case study with the 1000 genomes dataset as input.
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Leveraging the microbiome in host genome wide association studies
… Over the past decade, GWAS of human traits and diseases has revolutionized the field of complex disease genetics, identifying hundreds of genetic variants associated with several different phenotypes, ranging from metabolic diseases to cardiovascular and neuropsychiatric conditions. These …
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Blood Pressure, Arterial Stiffness and Cardiovascular Risk Prediction
… need to improve current cardiovascular (CV) disease risk prediction algorithms, allowing better stratification models for disease prevention and, ultimately, a personalised medicine approach. This is particularly important for ‘moderate risk’ individuals, where relatively few people will …
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Optimising Cardiovascular Disease Risk Assessment: Application of Dynamic Prediction Tools and Risk Stratification Strategies Using Electronic Health Records
Cardiovascular diseases (CVDs) remain the leading cause of morbidity and mortality worldwide. Identifying individuals who are at higher risk of CVD is fundamental for effectively implementing prevention strategies with limited health care resources and subsequently reducing the burden of CVD. For …