Artificial intelligence predicts undiagnosed atrial fibrillation in patients with embolic stroke of undetermined source using sinus rhythm electrocardiograms.

Journal: Heart rhythm
Published Date:

Abstract

BACKGROUND: Artificial intelligence (AI)-enabled sinus rhythm (SR) electrocardiogram (ECG) interpretation can aid in identifying undiagnosed paroxysmal atrial fibrillation (AF) in patients with embolic stroke of undetermined source (ESUS).

Authors

  • Jina Choi
    CHA University School of Medicine, 120, Haeryong-ro, Pocheon-si, Gyeonggi 13488, Korea.
  • Ju Youn Kim
    Division of Cardiology, Department of Internal Medicine, Heart Vascular Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.
  • Min Soo Cho
  • Minsu Kim
    School of Chemical and Biological Engineering, Institute of Chemical Processes, Seoul National University, Seoul 08826, Republic of 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.
  • Il-Young Oh
    Department of Internal Medicine, Seoul National University, Seoul National University Bundang Hospital, Seongnam, Republic of Korea. Electronic address: spy510@snu.ac.kr.
  • Youngjin Cho
    Department of Cardiology, Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam.
  • Ji Hyun Lee
    Division of Cardiology, Severance Cardiovascular Hospital, Yonsei University Health System, Seoul, Republic of Korea.