Outcome prediction of out-of-hospital cardiac arrest with presumed cardiac aetiology using an advanced machine learning technique.

Journal: Resuscitation
PMID: 31220514

Abstract

BACKGROUND: Outcome prediction for patients with out-of-hospital cardiac arrest (OHCA) has the possibility to detect patients who could have been potentially saved. Advanced machine learning techniques have recently been developed and employed for clinical studies. In this study, we aimed to establish a prognostication model for OHCA with presumed cardiac aetiology using an advanced machine learning technique.

Authors

  • Tomohisa Seki
    Department of Cardiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan; Department of Emergency and Critical Care Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan.
  • Tomoyoshi Tamura
    Department of Emergency and Critical Care Medicine, Keio University School of Medicine, Tokyo, Japan.
  • Masaru Suzuki
    Division of Respiratory Medicine, Department of Internal Medicine, Hokkaido University Graduate School of Medicine, Sapporo, Japan.

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