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Updated: Jul 4, 2025

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
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根据可解释的机器学习,对访问急诊室的败血症患者的早期死亡率预测:现实世界的多中心研究

Sang Won Park1,2, Na Young Yeo3, Seonguk Kang4

  • 1Department of Medical Informatics, School of Medicine, Kangwon National University, Chuncheon, Korea.

Journal of Korean medical science
|February 6, 2024
PubMed
概括

机器学习模型使用临床数据准确预测败血症死亡率. 基线变量提供比顺序器官衰竭评估 (SOFA) 得分更好的早期预测,识别关键预测因素.

关键词:
临床决策支持系统 (CDSS)可解释的人工智能 (XAI)机器学习 机器学习死亡率预测,败血症的预测

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