Distributed Training
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Federated Learning for Privacy-Preserving AI Model Training Across Distributed Healthcare Systems
Abstract: Building effective AI diagnostic tools in clinical environments presents a fundamental contradiction — the patient data most critical to model performance is precisely the data subject to the strictest legal and institutional restrictions. Regulations such as HIPAA and GDPR, while essential for protecting patient rights, render conventional centralized training pipelines largely impractical in real hospital settings where data cannot be transferred, pooled, or shared across institutional boundaries. This paper presents …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article