ADP-FL adapts differential privacy mechanisms in federated learning to achieve higher segmentation accuracy, better boundaries, faster convergence, and stability across skin, kidney, and brain imaging tasks while preserving privacy.
Privacy-preserving methods for health data analysis
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ADP-FL-MedSeg: Adaptive Differential Privacy for Federated Medical Segmentation Across Diverse Modalities
ADP-FL adapts differential privacy mechanisms in federated learning to achieve higher segmentation accuracy, better boundaries, faster convergence, and stability across skin, kidney, and brain imaging tasks while preserving privacy.