Development of a Visualization Deep Learning Model for Classifying Origins of Ventricular Arrhythmias.

Journal: Circulation journal : official journal of the Japanese Circulation Society
PMID: 35387940

Abstract

BACKGROUND: Several algorithms have been proposed for differentiating the right and left outflow tracts (RVOT/LVOT) arrhythmia origins from 12-lead electrocardiograms (ECGs); however, the procedure is complicated. A deep learning (DL) model, a form of artificial intelligence, can directly use ECGs and depict the importance of the leads and waveforms. This study aimed to create a visualized DL model that could classify arrhythmia origins more accurately.

Authors

  • Kazutaka Nakasone
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Makoto Nishimori
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Hospital, 7-5-2, Kusunoki-Cho, Chuo-Ku, Kobe, Japan.
  • Kunihiko Kiuchi
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Hospital, 7-5-2, Kusunoki-Cho, Chuo-Ku, Kobe, Japan. kiuchi@med.kobe-u.ac.jp.
  • Masakazu Shinohara
    Division of Epidemiology, Kobe University Graduate School of Medicine, Kobe, Japan.
  • Koji Fukuzawa
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Hospital, 7-5-2, Kusunoki-Cho, Chuo-Ku, Kobe, Japan.
  • Mitsuru Takami
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Hospital, 7-5-2, Kusunoki-Cho, Chuo-Ku, Kobe, Japan.
  • Mustapha El Hamriti
    Clinic of Electrophysiology, Heart and Diabetes Center NRW, University Hospital of Ruhr-University Bochum, Bochum, Germany.
  • Philipp Sommer
    Clinic of Electrophysiology, Heart and Diabetes Center NRW, University Hospital of Ruhr-University Bochum, Bochum, Germany.
  • Jun Sakai
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Toshihiro Nakamura
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Atsusuke Yatomi
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Yusuke Sonoda
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Hiroyuki Takahara
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Kyoko Yamamoto
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Yuya Suzuki
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Kenichi Tani
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Hidehiro Iwai
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Yusuke Nakanishi
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Graduate School of Medicine.
  • Ken-Ichi Hirata
    Division of Cardiovascular Medicine, Department of Internal Medicine, Kobe University Hospital, 7-5-2, Kusunoki-Cho, Chuo-Ku, Kobe, Japan.

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