Explainable machine learning for early prediction of sepsis in traumatic brain injury: A discovery and validation study.

Journal: PloS one
PMID: 39527609

Abstract

BACKGROUND: People with traumatic brain injury (TBI) are at high risk for infection and sepsis. The aim of the study was to develop and validate an explainable machine learning(ML) model based on clinical features for early prediction of the risk of sepsis in TBI patients.

Authors

  • Wenchi Liu
    Department of Trauma Center/Emergency Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Xing Yu
    Department of Geriatrics, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Jinhong Chen
    Department of Trauma Center/Emergency Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Weizhi Chen
    Department of Trauma Center/Emergency Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Qiaoyi Wu
    Department of Trauma Center/Emergency Surgery, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.

Keywords

External Resources

Popular Topics
Recent Journals