The project is on federated learning in biomedical applications, and will focus on statistical learning in healthcare in compliance with anonymity, security and non-transferability of data across centers. Fed-BioMed will tackle this challenge through methodological, technical, and translational advances. The project will allow us to exploit data for thousands of individuals from two of the largest existing multi-centric studies: imaging-genetics analysis in the ENIGMA consortium and sudden cardiac death prediction from a network of French clinical sites.
Non invasive cardiac personalisation
Simulation of ventricular tachycardia re-entry circuit
heartMeshFine
Electrophysiology
Cardiac Fibres from in vivo Diffusion Tensor Imaging
