An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.

Journal: Respiratory research
PMID: 38890628

Abstract

BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients.

Authors

  • Dong Huang
    Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology, Shenzhen, GuangDong, China.
  • Linjing Gong
    Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan, 610041, China.
  • Chang Wei
    School of Arts and Media, Suqian University, Suqian, China.
  • Xinyu Wang
    Department of Endocrinology, Institute of Translational Medicine, Health Science Center, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, Guangdong, China.
  • Zongan Liang
    Department of Respiratory and Critical Care Medicine, West China Hospital, Sichuan University, No. 37 Guoxue Alley, Chengdu, Sichuan, 610041, China. liangza@scu.edu.cn.

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