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 20 of 173 for “"Risk Prediction"”.
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Risk prediction with genomic data
… 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 Study …
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A universal outbreak risk prediction tool
… this new situation, the ability to predict the risk of pandemic outbreaks is a necessary. Existing prediction tools include machine learning-based tools and mathematical tools, which do not use machine learning. They both have disadvantages and advantages. My research goal is to develop an ideal …
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A NOVEL MULTI-ETHNIC STROKE RISK PREDICTION MODEL
Stroke risk prediction modeling allows for the identification of individuals who are at heightened stroke risk, which is an important first step in targeted preventive measures. Current stroke risk models are not fully generalizable to multi-ethnic populations because the most widely used one is …
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Blood Pressure, Arterial Stiffness and Cardiovascular Risk Prediction
… 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 suffer a CV …
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Type-1 diabetes risk prediction using multiple kernel learning
… kernel learning (MKL) for type-1 diabetes risk prediction. MKL combines different models and representation of data to find a linear combination of these representations of the data. MKL has been successfully been implemented in image detection, splice site detection, ribosomal and membrane …
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Development of a Risk Prediction Tool for Emergency Laparotomy
Aim: This thesis aims to develop a risk prediction tool for emergency laparotomy surgery based on easily obtainable preoperative variables that predict useful outcomes for clinicians and patients. Methods: A systematic review was used to establish individual risk factors for emergency laparotomy. …
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Approaches to developing clinically useful Bayesian risk prediction models
Prediction of the presence of disease (diagnosis) or an event in the future course of disease (prognosis) becomes increasingly important in the current era of personalised medicine. Both tasks (diagnosis and prognosis) are supported using (risk) prediction models. Such models usually combine …
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Risk prediction models for hip fracture: parametric versus Cox regression
… due to high morbidity, mortality and cost. Risk prediction models can aid clinical decision-making by identifying individuals at risk. Objective: To build risk prediction model for incident hip fracture using Weibull regression and compare this with Cox regression model. Method: The Study of …
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Cardiovascular disease risk prediction models: does one-score-fit-all?
… and severe COVID-19 are particularly at elevated risk of developing CVD, highlighting the need for precise and equitable risk prediction tools. The changing landscape of CVD, partly due to the COVID-19 pandemic disrupting patterns of CVD incidence and care delivery, and partly due to the rising …
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Evaluating and enhancing cardiovascular disease risk prediction with algorithmic fairness
… 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 inequities. Algorithmic fairness, a research …
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Cancer risk prediction with next generation sequencing data using machine learning
… detected with SAMtools and GATK achieve similar prediction accuracies. It is also noted that the features that are ranked with the PCC yield better accuracy than the chi-square test. In all of the analyses, the SNPs are identified to have superior accuracy as compared to the INDELs or the full …
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Essays on economic value of intraday covariation estimators for risk prediction
… portfolio optimization, volatility trading and risk management. More recently, volatility of asset returns was once again under spotlight during the 2008-2009 nancial crisis. One of the most visible indicators of the crisis that captured the attention of the nancial in- dustry was the extremely …
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Clustering-Based Methods for Clinical Risk Prediction of Rare Missense Variants
… are more challenging to classify. Improving predictions of such variants has the potential to lead to clinically actionable solutions for individual patients. In this paper, we develop and evaluate several new clustering-based approaches for predicting the clinical risk of rare missense …
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Aircraft Bird Strike Risk Prediction Using Machine Learning and Analytic Hierarchy Process
… Atmospheric Administration alongside bird strike risk using Long Short-Term Memory Recurrent Neural Network (LSTM-RNN), XGBoost regression tree, and Bayesian network algorithms. Five years of bird strike data from four geographically diverse airfields served as the target risk variable, …
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Risk Prediction and Value of Polygenic Risk Scores in Colorectal Cancer Screening
Risk prediction models that are based on common genetic variants, known as Polygenic risk Score (PRS), have shown promises to guide personalized screening for colorectal cancer (CRC). Continuous efforts to improve PRS risk prediction are needed for clinical use, and understanding its added value of …
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Risk prediction models for binary response variables for the coronary bypass operation
… trials. This thesis focuses on setting up risk stratification algorithms. Utilizing the binary feature of the response variables, logistic regression analyses and classification trees (recursive partitioning) were used with the variables identified by the Health Data Research Institute in …
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Essays on the economic value of intraday covariation estimators for risk prediction
… portfolio optimization, volatility trading and risk management. More recently, volatility of asset returns was once again under spotlight during the 2008-2009 financial crisis. The study contributes to the extant volatility forecasting literature in three areas. First, it addresses the question …
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Machine learning models for functional impairment risk prediction in ischemic stroke patients
Background: Stroke-related functional impairment risk scores are commonly used to estimate the patient-specific risk of functional impairment in acute care settings. However, these models have been primarily developed based on regression models, which might not provide optimal predictive accuracy, …
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