Explainable artificial intelligence to detect atrial fibrillation using electrocardiogram.

Journal: International journal of cardiology
Published Date: Dec 1, 2020

Abstract

INTRODUCTION: Early detection and intervention of atrial fibrillation (AF) is a cornerstone for effective treatment and prevention of mortality. Diverse deep learning models (DLMs) have been developed, but they could not be applied in clinical practice owing to their lack of interpretability. We developed an explainable DLM to detect AF using ECG and validated its performance using diverse formats of ECG.

Authors

  • Yong-Yeon Jo
    Medical research team, Medical AI, Seoul, South Korea.
  • Younghoon Cho
    Medical Research and Development Center, Bodyfriend, Seoul, South Korea.
  • Soo Youn Lee
    Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul 110799, South Korea.
  • Joon-Myoung Kwon
    Department of Emergency Medicine, Mediplex Sejong Hospital, Incheon, Korea.
  • Kyung-Hee Kim
    Department of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.
  • Ki-Hyun Jeon
    Department of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Korea.
  • Soohyun Cho
    Medical Research and Development Center, Bodyfriend, Seoul, South Korea.
  • Jinsik Park
    Department of Cardiology, Mediplex Sejong Hospital, Incheon, Korea.
  • Byung-Hee Oh
    Division of Cardiology, Cardiovascular Center, Mediplex Sejong Hospital, Incheon, Republic of Korea.

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