Medicine and Health
Towards fairness-aware and privacy-preserving enhanced collaborative learning for healthcare
F. Zhang, D. Zhai, et al.
Federated Learning can harness distributed patient data while preserving privacy, but disparities in computing resources risk unequal AI outcomes. We introduce a resource-adaptive collaborative learning framework that dynamically matches varying institutional capacities to improve model accuracy and fairness. This research was conducted by Feilong Zhang, Deming Zhai, Guo Bai, Junjun Jiang, Qixiang Ye, Xiangyang Ji, and Xianming Liu.
~3 min • Beginner • English
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