Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts

A novel Federated Evidential Active Learning (FEAL) method that leverages both aleatoric and epistemic uncertainties in global and local models to effectively select informative samples for annotation in federated learning scenarios with domain shifts.