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.
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Showing 1 to 19 of 19 for “"disease prediction"”.
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Large scale disease prediction
… the foundation of an automated large-scale disease prediction system. Unlike previous work that has typically focused on a small self-contained dataset, we explore the possibility of combining a large amount of heterogeneous data to perform gene selection and phenotype classification. First, …
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Enhancing Microbiome Host Disease Prediction with Variational Autoencoders
… implicate further potential for progress in disease diagnosis and treatment in humans. The ability to classify a human microbiome profile into a disease category, and additionally identify the differentiating factors within the profile between diseased and healthy individuals are valuable …
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Microbial, immunological, phenotypic and genetic markers of risk: aspects of Crohn’s disease that are shared by unaffected siblings
Crohn’s disease (CD) is an incurable intestinal disorder in which an immune response driven by commensal gut microbiota leads to chronic inflammation. Why this occurs in specific individuals is unclear; however, a genetic predisposition is fundamental and relatives of patients with CD are at …
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Learning to Improve Clinical Decisions and AI Safety by Leveraging Structure
… of external knowledge to guide model predictions. Additionally, we develop differentially private (DP) training techniques using gradient structure to mitigate privacy leakage. In this thesis, we develop methods on different medical modalities such as multivariate physiological signals …
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Machine learning enhancements for wearable device investigation of acute anxiety and cardiovascular diseases
… activity (EDA) etc. signals, to improve early disease prediction and progression in physical and mental health disorders. We measure our ability to use these signals to classify anomalies in the cardiovascular health and physiological body reactions in persons with disorders. This thesis is a …
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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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Addressing Deficiencies from Missing Data in Electronic Health Records
… outcomes. In particular, EHRs have been used for disease prediction, data-driven clinical decision support, patient trajectory modeling, etc. However, it is common that EHRs data contain substantial missing information that could make the clinical prediction tasks more challenging if left …
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Linear mixed model for multi-level omics data
Accurate disease prediction is expected to facilitate the precision medicine with emerging genetic findings and other demonstrated knowledge (Ashley, 2015). While rare genetic variants, multi-omic information and family structure have provided unprecedented data resources for predictive studies, …
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Predicting Task Functional Localizers Using Naturalistic fMRI
… for predicting individual traits, biomarkers of disease and functional brain localizations, potentially offering advantages over traditional resting-state approaches. This study investigated the use of interpretable deep learning models to predict demographics and functional task localizer …
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Inoculum pattern and relationship between incidence of black root rot of tobacco and inoculum density of Thielaviopsis basicola in field soil
… of tobacco or chemicals. In order to develop a disease prediction program, disease-inoculum density relationships must be determined. It was the purpose of this study to develop an improved procedure for estimating the populations of T. basicola in naturally infested soil. A second objective was …
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Detection of Genes Influencing Chronic and Mendelian Disease Via Loss-of-Function Variation
… the contribution of LOF variation to health and disease within the general population remains largely uncharacterized.</p> <p>Using whole exome sequence from 8,554 participants in the Atherosclerosis Risk in Communities (ARIC) study, we explored the impact of LOF variation on a broad spectrum of …
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Multiscale Modelling of Environmentally Transmitted Infectious Diseases
… in predicting the dynamics of infectious disease systems. Yet, there is still a lack of evidence that generally indicates which among the different categories of multiscale models of infectious disease systems is more appropriate to use in multiscale modelling of infectious disease systems …
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Predicting progressions and clinical subtypes of Alzheimer’s disease using machine learning
Alzheimer’s disease is a degenerative brain disease which impairs a person’s ability to perform day to day activities. Research has shown AD to be a heterogeneous condition, having a high variation in terms of the symptoms and disease progression rate. Treating Alzheimer's disease (AD) is …
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A Predictive Analysis of Electronic Healthcare Records for Stroke Symptoms
… focused on prevention and early treatment of disease by analysing different factors. However, a high volume of medical data, heterogeneity, and complexity have become the biggest challenges in stroke symptoms prediction. Algorithms with very high level of accuracy are, therefore, vital for …
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Bioinformatic and molecular approaches for the analysis of the retinal pigment epithelium (RPE) transcriptome
… genes underlying susceptibility to complex human diseases because of the potential utility of such genes in disease prediction and therapy. The complex age-related macular degeneration (AMD) is a prevalent cause of legal blindness in industrialized countries and predominantly affects the elderly …
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Triggers of autoimmunity. Studies on gestational events.
… diabetes have a higher risk of developing celiac disease (CD), an additional aim was to determine whether markers of possible infections during early pregnancy was associated with development of tissue transglutaminase (tTG) autoantibodies or CD in the offspring. These aims have been summarized in …
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Alternaria Leaf Blight and Head Rot of Broccoli: UAV-Based Disease Detection and Fungicide Resistance Management
… Additionally, knowledge gaps exist regarding disease-tolerant broccoli cultivars, the extent of QoI fungicide compromise in Virginia, and effective alternative control measures. Disease monitoring is crucial for timely detection of pathogens and fungicide program failures. Multispectral …
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Machine Learning Methods for Decision Making Inference in Healthcare
… COVID-19 and Influenza-like Illnesses (ILI) predictions. In Chapter 3, I will investigate two treatment-related decision-making problems using electronic healthcare records (EHRs) databases. In Chapter 3 section 1, I will introduce a unified propensity score method for causal inference …