Herclassificatie van individuen via multi-view data in het licht van confounders

To develop a framework for gene-centric image data integration analytics and support a patient stratification strategy that identifies major gene effects with potential applications in a variety of medical disorders. This expands our previous work on rare monogenetic/ complex diseases in craniofacial and neurodevelopmental disorders, using available extensive datasets of different imaging modalities on individuals and patient groups. Mathematics, statistical genetics and deep learning in image analysis (potentially non-linear data-dependencies) will enable data-driven phenotyping from images for patient diagnostics, and stratified screening/subtyping.