Machine Learning-Based Mortality Prediction for Acute Gastrointestinal Bleeding Patients Admitted to Intensive Care Unit.

Journal: Current medical science
PMID: 40014197

Abstract

OBJECTIVE: The study aimed to develop machine learning (ML) models to predict the mortality of patients with acute gastrointestinal bleeding (AGIB) in the intensive care unit (ICU) and compared their prognostic performance with that of Acute Physiology and Chronic Health Evaluation II (APACHE-II) score.

Authors

  • Zhou Liu
    Department of Radiology, National Cancer Center/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
  • Liang Zhang
  • Gui-Jun Jiang
    Department of Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
  • Qian-Qian Chen
    Department of Gastroenterology, The First Medical Center of Chinese PLA General Hospital, Beijing 100853, China. qian_qian_chen@163.com.
  • Yan-Guang Hou
    Department of Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, 430060, China.
  • Wei Wu
    Department of Pharmacy, The First Affiliated Hospital, Fujian Medical University, Fuzhou, China.
  • Muskaan Malik
    The First Clinical Medical School of Wuhan University, Wuhan, 430060, China.
  • Guang Li
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
  • Li-Ying Zhan
    Department of Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, 430060, China. zhanliying@whu.edu.cn.

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