MR-based predictive modelling of clinical outcomes using machine learning

We develop methods and application for prediction of clinical outcomes such as memory performance and biomarker positivity using structural brain morphometry images. We focus on non-parametric methods such as Gaussian process (GP) Regression and Classification. We validate the approaches in context of the DZNE DELCODE cohort and validate the predictions using longitudinal data.