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Updated: May 5, 2026

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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一个可解释的基于机器学习的模型,用于预测社区获得性肺炎和结缔组织疾病患者的重症监护病房入院情况

Dong Huang1, Linjing Gong1, Chang Wei1

  • 1Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan, 610041, China.

Respiratory research
|June 18, 2024
PubMed
概括

这项研究开发了一种XGBoost机器学习模型,用于预测社区获得性肺炎 (CAP) 和结缔组织疾病 (CTD) 患者的重症监护室 (ICU) 入院情况. 该模型准确识别高风险患者,帮助临床决策.

关键词:
在社区获得的肺炎.结合性组织疾病 结合性组织疾病在重症监护病房的重症监护病房.机器学习是机器学习.预测模型的预测模型.风险因素 风险因素

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