在败血症预测风险评分中,在不降低性能的情况下提高了可解释性

Adam Kotter1, Samir Abdelrahman1, Yi-Ki Jacob Wan1

  • 1Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, USA.

PubMed
概括

一个新的整数评分系统,STEWS,与复杂的机器学习模型的预测性能相匹配,用于在非重症监护病房预测败血症. 这提高了解释性,而不会牺牲早期败血症检测的准确性.

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