Construction and validation of prognostic model for ICU mortality in cardiac arrest patients: an interpretable machine learning modeling approach.

Journal: European journal of medical research
PMID: 40275415

Abstract

BACKGROUND: The incidence and mortality of cardiac arrest (CA) is high. We developed interpretable machine learning models for early prediction of ICU mortality risk in patients diagnosed with CA.

Authors

  • Yong Li
    Department of Surgical Sciences, Western Michigan University Homer Stryker M.D. School of Medicine, Kalamazoo, MI, United States.
  • Ying Liu
    The First School of Clinical Medicine, Lanzhou University, Lanzhou, China.
  • Qing Zhang
    Department of Respiratory Medicine, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
  • Hongwei Zhu
    Department of Hepatopancreatobiliary Surgery, The Third Xiangya Hospital, Central South University, Changsha, Hunan, P.R. China.
  • Chengli Wen
    Department of Intensive Care Medicine, Department of Critical Care Medicine, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
  • Xian Jiang
    Puer University, Puer 665000, China.

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