Deep-learning-based out-of-hospital cardiac arrest prognostic system to predict clinical outcomes.

Journal: Resuscitation
PMID:

Abstract

AIM: Out-of-hospital cardiac arrest (OHCA) is a major healthcare burden, and prognosis is critical in decision-making for treatment and the withdrawal of life-sustaining therapy. This study aimed to develop and validate a deep-learning-based out-of-hospital cardiac arrest prognostic system (DCAPS) for predicting neurologic recovery and survival to discharge.

Authors

  • Joon-Myoung Kwon
    Department of Emergency Medicine, Mediplex Sejong Hospital, Incheon, Korea.
  • Ki-Hyun Jeon
    Department of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.
  • Hyue Mee Kim
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.
  • Min Jeong Kim
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.
  • Sungmin Lim
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.
  • Kyung-Hee Kim
    Department of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.
  • Pil Sang Song
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.
  • Jinsik Park
    Department of Cardiology, Mediplex Sejong Hospital, Incheon, Korea.
  • Rak Kyeong Choi
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.
  • Byung-Hee Oh
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.