Artificial intelligence to predict needs for urgent revascularization from 12-leads electrocardiography in emergency patients.

Journal: PloS one
PMID: 30625197

Abstract

BACKGROUND: Patient with acute coronary syndrome benefits from early revascularization. However, methods for the selection of patients who require urgent revascularization from a variety of patients visiting the emergency room with chest symptoms is not fully established. Electrocardiogram is an easy and rapid procedure, but may contain crucial information not recognized even by well-trained physicians.

Authors

  • Shinichi Goto
    Division of General Internal Medicine & Family Medicine, Department of General and Acute Medicine, Tokai University School of Medicine, Isehara, Japan.
  • Mai Kimura
    Department of Cardiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
  • Yoshinori Katsumata
    Department of Cardiology, Keio University School of Medicine, Tokyo, Japan.
  • Shinya Goto
    Department of Medicine (Cardiology), Tokai University School of Medicine, Isehara, Japan.
  • Takashi Kamatani
    Pulmonary Division, Department of Medicine, Keio University School of Medicine, 35 Shinanomachi Shinjuku-ku, Tokyo 160-8582, Japan.
  • Genki Ichihara
    Department of Cardiology, Keio University School of Medicine, Tokyo, Japan.
  • Seien Ko
    Department of Cardiology, Keio University School of Medicine, Tokyo, Japan.
  • Junichi Sasaki
    Department of Emergency and Critical Care Medicine, Keio University School of Medicine, Tokyo, Japan.
  • Keiichi Fukuda
    Department of Cardiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo 160-8582, Japan.
  • Motoaki Sano
    Department of Cardiology, Keio University School of Medicine, Tokyo, Japan.

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