Achieving flexible fairness metrics in federated medical imaging

Achieving flexible fairness metrics in federated medical imaging

Abstract The rapid adoption of Artificial Intelligence (AI) in medical imaging raises fairness and privacy concerns across demographic groups, especially in diagnosis and treatment decisions. While federated learning (FL) offers decentralized privacy preservation, current frameworks often prioritize...

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Main Authors: Huijun Xing, Rui Sun, Jinke Ren, Jun Wei, Chun-Mei Feng, Xuan Ding, Zilu Guo, Yu Wang, Yudong Hu, Wei Wei, Xiaohua Ban, Chuanlong Xie, Yu Tan, Xian Liu, Shuguang Cui, Xiaohui Duan, Zhen Li
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-025-58549-0
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