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Updated: Jul 10, 2025

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提高电子健康记录人工智能模型的公平性:联合学习方法的案例

Raphael Poulain1, Mirza Farhan Bin Tarek1, Rahmatollah Beheshti1

  • 1University of Delaware USA.

FAccT '23 : Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery
|November 22, 2023
PubMed
概括

在医疗保健中开发公平的人工智能至关重要. 这项研究引入了一种联合学习方法,使用对抗式调解来减轻健康AI模型的偏差,提高公平性而不会显著影响准确性.

关键词:
竞争性的公平性 竞争性的公平性算法公平性 算法公平性联合学习学习 (Federated Learning) 是一种联合学习.

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