Deep-learning model for screening sepsis using electrocardiography.

Journal: Scandinavian journal of trauma, resuscitation and emergency medicine
Published Date: Oct 3, 2021

Abstract

BACKGROUND: Sepsis is a life-threatening organ dysfunction and a major healthcare burden worldwide. Although sepsis is a medical emergency that requires immediate management, screening for the occurrence of sepsis is difficult. Herein, we propose a deep learning-based model (DLM) for screening sepsis using electrocardiography (ECG).

Authors

  • Joon-Myoung Kwon
    Department of Emergency Medicine, Mediplex Sejong Hospital, Incheon, Korea.
  • Ye Rang Lee
    Medical Research Team, Medical AI, Co., Seoul, Republic of Korea.
  • Min-Seung Jung
    Medical Research Team, Medical AI Co. Ltd., Seoul, South Korea.
  • Yoon-Ji Lee
    Medical Research Team, Medical AI Co. Ltd., Seoul, South Korea.
  • Yong-Yeon Jo
    Medical research team, Medical AI, Seoul, South Korea.
  • Da-Young Kang
    Artificial Intelligence and Big Data Research Center, Sejong Medical Research Institute, 20, Gyeyangmunhwa-ro, Gyeyang-gu, Incheon, Republic of Korea.
  • Soo Youn Lee
    Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, South Korea.
  • Yong-Hyeon Cho
    Medical Research Team, Medical AI Co. Ltd., Seoul, South Korea.
  • Jae-Hyun Shin
    Medical Research Team, Medical AI Co. Ltd., Seoul, South Korea.
  • Jang-Hyeon Ban
    Medical R&D Center, Bodyfriend Co. Ltd., Seoul, South Korea.
  • Kyung-Hee Kim
    Department of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.

Keywords

External Resources

Popular Topics
Recent Journals