H. R.

A Divergence-Aware Personalized Federated Transformer Framework for Privacy-Preserving Multi-Center Medical Image Intelligence

In a non-IID medical imaging scenario, the problems that occur in federated learning (FL) include high data variability, data leakage, convergence instability, and suboptimal global aggregation. The number of medical imaging applications is vast, and Federated Learning (FL) has already been used in many of them; some m...