Interpretable prediction of hospital mortality in bleeding critically ill patients based on machine learning and SHAP.

Journal: BMC medical informatics and decision making
Published Date: Jul 15, 2025

Abstract

BACKGROUND: Hemorrhage is a prevalent and critical condition in the intensive care unit (ICU), characterized by high incidence, elevated mortality rates, and substantial therapeutic challenges. Accurate prediction of mortality in patients with hemorrhage is essential for developing personalized prevention and treatment strategies. Nevertheless, the implementation of effective predictive models in clinical practice remains limited, primarily due to the lack of robust and interpretable tools.

Authors

  • Bingkui Ren
    Department of Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, People's Republic of China.
  • Yuping Zhang
    School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China.
  • Siying Chen
    School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China.
  • Jinglong Dai
    Department of Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, People's Republic of China.
  • Junci Chong
    Department of Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, People's Republic of China.
  • Yifei Zhong
    Beijing Hospital, Institute of Geriatric Medicine, Peking University Fifth School of Clinical Medicine, Beijing, China.
  • Mengkai Deng
    Beijing Hospital, Institute of Geriatric Medicine, Peking University Fifth School of Clinical Medicine, Beijing, China.
  • Shaobo Jiang
    Department of Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, P.R. China.
  • Zhigang Chang
    Department of Critical Care Medicine, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, People's Republic of China. zhigangchang@hotmail.com.

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