Prediction of Neurological Outcomes in Out-of-hospital Cardiac Arrest Survivors Immediately after Return of Spontaneous Circulation: Ensemble Technique with Four Machine Learning Models.

Journal: Journal of Korean medical science
PMID: 34282605

Abstract

BACKGROUND: We performed this study to establish a prediction model for 1-year neurological outcomes in out-of-hospital cardiac arrest (OHCA) patients who achieved return of spontaneous circulation (ROSC) immediately after ROSC using machine learning methods.

Authors

  • Ji Han Heo
    Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea.
  • Taegyun Kim
    Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea.
  • Jonghwan Shin
    Department of Emergency Medicine, Seoul National University College of Medicine, Seoul, Korea.
  • Gil Joon Suh
    Department of Emergency Medicine, Seoul National University Hospital, Seoul, Korea.
  • Joonghee Kim
    Department of Emergency Medicine, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620, Republic of Korea.
  • Yoon Sun Jung
    Division of Critical Care Medicine, Seoul National University Hospital, Seoul, Korea.
  • Seung Min Park
    Department of Emergency Medicine, Seoul National University Bundang Hospital, 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620, Republic of Korea.
  • Sungwan Kim
    Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Republic of Korea.

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