THE WORK
From heterogeneous patient data to clinically meaningful phenotypes
The team prepared and analyzed large-scale UK Biobank data, combining demographic, clinical, laboratory and imaging-derived variables. Hierarchical clustering with Ward's minimum variance method was used to identify patient subgroups, followed by survival analysis to assess outcome differences.
The project also explored image-derived representations from cardiac MRI using a convolutional autoencoder and compared image-based clusters with clusters derived from clinical data.