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Updated: Jul 2, 2025

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实现全球模型通用性:使用OHDSI网络对患者一级风险预测模型进行独立的跨站点特征评估

Behzad Naderalvojoud1, Catherine M Curtin2, Chen Yanover3

  • 1Department of Medicine, Stanford University, Stanford, CA 94305, United States.

Journal of the American Medical Informatics Association : JAMIA
|February 27, 2024
PubMed
概括

这项研究使用来自四个国家的电子健康记录开发了术后长期使用阿片类药物 (POU) 的可概括的预测模型. 跨站点特征选择在外部验证中显著改善了模型性能,提高了医疗保健模型的实用性.

关键词:
功能选择 功能选择机器学习是机器学习.模型的概括性模型的概括性.阿片类药物风险的风险长时间使用阿片类药物手术 手术 手术 手术 手术 手术 手术

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