Principal Investigator: Professor Thomas Nichols
Institution: University of OxfordTags: 34077, multivariate statistical machine learning, neuroimaging-statistics, population-neuroimaging
Methods to allow joint analysis across the UK Biobank’s many imaging, genomic, environmental and clinical variables and remains challenging and underdeveloped. We will develop scalable multivariate statistical machine learning methods and software to extract useful features from all imaging UK Biobank different data modalities simultaneously to a) to predict different health outcomes from imaging and non-imaging, b) associate brain features with non-brain factors while controlling for individual differences in environmental and genomic data, and c) use UK Biobank data as a replacement for Monte Carlo simulations in the evaluation and benchmarking of new and existing analyses methods.
Our work will assist scientist in extracting features from the multitude of UK Biobank variables, and finding relationships among these features, ultimately supporting the UK Biobank aims to improve the prevention, diagnosis of disease. We will develop methods and software that uses the shared information among different data modalities in the UK Biobank to extract features, ultimately building models to predict different health outcomes and associate brain related features with non-imaging variables. We will also use the UK biobank data to benchmark the performance of statistical methods that researchers use every day.