This research aims to advance the field of federated learning by addressing privacy, domain shifts, and personalization challenges, particularly in the context of mobile and digital healthcare. By developing robust and scalable solutions, the proposed framework has the potential to significantly enhance patient care, diagnostics, and personalized treatment while maintaining stringent privacy standards
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