Personalized federated learning for medical vision-language models via efficient fine-tuning and uncertainty-aware disentanglement
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Privacy concerns and data heterogeneity remain critical barriers to advancing medical AI. While federated learning (FL) offers a decentralized solution, it often suffers from the Subspace Mismatch problem in clinical settings, where non-independent and identic... ...
