Development of a machine learning model for the prediction of the short-term mortality in patients in the intensive care unit.

Journal: Journal of critical care
PMID: 35834893

Abstract

PURPOSE: The aim of this study was to develop and evaluate a machine learning model that predicts short-term mortality in the intensive care unit using the trends of four easy-to-collect vital signs.

Authors

  • Jaeyoung Yang
    Department of Anesthesiology and Pain Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea.
  • Hong-Gook Lim
    Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea. Electronic address: hongklim@hanmail.net.
  • Wonhyeong Park
    Department of Internal Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea.
  • Dongseok Kim
    Department of Anesthesiology and Pain Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea.
  • Jin Sun Yoon
    Department of Anesthesiology and Pain Medicine, Veterans Health Service Medical Center, Seoul, Republic of Korea.
  • Sang-Min Lee
    Department of Orthopedics, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Kwangsoo Kim
    Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital, Seoul, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals