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Updated: Jan 10, 2026

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开发和验证一个公平的机器学习模型,以识别在电子健康记录数据中具有高护理连续性的患者

Yao An Lee1, Tiange Tang2, Yu Huang3,4,5,6

  • 1Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, FL, USA.

medRxiv : the preprint server for health sciences
|November 26, 2025
PubMed
概括

电子健康记录 (EHR) 数据的不连续性可能导致错误分类. 开发了一种机器学习模型,以预测EHR的连续性,提高跨种族群体的公平性和加强EHR研究.

关键词:
数据连续性的数据连续性.欧洲人权理事会 欧洲人权理事会机器学习预测的预测.

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