Developing a rapid screening tool for high-risk ICU patients of sepsis: integrating electronic medical records with machine learning methods for mortality prediction in hospitalized patients-model establishment, internal and external validation, and visualization.

Journal: Journal of translational medicine
PMID:

Abstract

OBJECTIVES: To develop a machine learning-based prediction model using clinical data from the first 24 h of ICU admission to enable rapid screening and early intervention for sepsis patients.

Authors

  • Songchang Shi
    Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Lihui Zhang
    College of Civil Engineering and Architecture, Zhejiang University, 866, Yuhangtang Road, Hangzhou, 310058, China.
  • Shujuan Zhang
    College of Agricultural Engineering, Shanxi Agriculture University, Jinzhong 030801, China.
  • Jinyang Shi
    Fujian Medical University, Fuzhou, 350001, People's Republic of China.
  • Donghuang Hong
    Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, 350001, People's Republic of China.
  • Siqi Wu
    Research Center, The Seventh Affiliated Hospital of Sun Yat-sen University, Shenzhen 518107, China.
  • Xiaobin Pan
    Department of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital South Branch, Fujian Provincial Hospital, Fuzhou University Affiliated Provincial Hospital, Fuzhou, 350001, People's Republic of China.
  • Wei Lin
    Department of Geriatric Rehabilitation, Jiangbin Hospital, Nanning, China.