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Updated: May 10, 2025

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通过可解释的机器学习和电子健康记录中的错误处理来改善临床决策支持

Mehak Arora1,2, Hassan Mortagy3, Nathan Dwarshuis3

  • 1Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27708, United States.

Journal of the American Medical Informatics Association : JAMIA
|April 22, 2025
PubMed
概括

我们开发了Trust-MAPS,这是一个新的工具,通过结合临床背景来增强机器学习 (ML) 的电子医疗记录 (EMR) 数据处理. 这提高了15%的败血症预测准确度,并增加了模型的解释性.

关键词:
临床数据的预处理.临床决策支持 临床决策支持情境感知算法是指情境感知算法.可以解释的机器学习.异常标志的检测异常标志的检测

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