medical machine learning
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Federated Intelligence for Privacy-Preserving Health Data Analytics
Abstract: Healthcare artificial intelligence is limited by a structural conflict: useful models benefit from diverse multi-institutional data, while clinical records cannot be freely pooled because of privacy, ownership and governance constraints. This study presents a practical federated-learning framework for privacy-preserving health data analytics and validates its basic learning behavior in a reproducible cross-silo simulation. Five non-identical institutional clients were created from the public Breast Cancer Wisconsin (Diagnostic) dataset, and a standardized …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 3, 2026 Read article