Deep learning models for the prediction of intraoperative hypotension.

Journal: British journal of anaesthesia
PMID: 33558051

Abstract

BACKGROUND: Intraoperative hypotension is associated with a risk of postoperative organ dysfunction. In this study, we aimed to present deep learning algorithms for real-time predictions 5, 10, and 15 min before a hypotensive event.

Authors

  • Solam Lee
    Department of Dermatology and Preventive Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
  • Hyung-Chul Lee
    From the Department of Anesthesiology and Pain Medicine, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Korea.
  • Yu Seong Chu
    Department of Biomedical Engineering, Yonsei University, Wonju, Republic of Korea.
  • Seung Woo Song
    Department of Anaesthesiology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
  • Gyo Jin Ahn
    Department of Emergency Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
  • Hunju Lee
    Department of Preventive Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.
  • Sejung Yang
    Medical Physics Division, Department of Radiation Oncology, Stanford University School of Medicine, Palo Alto, United States of America.
  • Sang Baek Koh
    Department of Preventive Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea.

Keywords

External Resources

Popular Topics
Recent Journals