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Updated: Jun 27, 2025

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分析个性化对医疗保健联合学习中的公平性影响

Tongnian Wang1, Kai Zhang2, Jiannan Cai3

  • 1Department of Information Systems and Cyber Security, The University of Texas at San Antonio, San Antonio, 78249 TX USA.

Journal of healthcare informatics research
|April 29, 2024
PubMed
概括

个性化联合学习 (FL) 提高了医疗预测的准确性和公平性,而不是独立模型,但并不总是超越标准FL. 它可以帮助有偏见的医院,但可能会使不那么有偏见的医院的公平性恶化.

关键词:
联合学习是联合学习.集团的公平性 集团的公平性在健康方面存在差异.个性化 个性化隐私 隐私 隐私 隐私 隐私 隐私

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