Artificial intelligence-derived electrocardiographic aging and risk of atrial fibrillation: a multi-national study.

Journal: European heart journal
PMID:

Abstract

BACKGROUND AND AIMS: Artificial intelligence (AI) algorithms in 12-lead electrocardiogram (ECG) provides promising age prediction methods. This study investigated whether the discrepancy between ECG-derived AI-predicted age (AI-ECG age) and chronological age, termed electrocardiographic aging (ECG aging), is associated with atrial fibrillation (AF) risk.

Authors

  • Seunghoon Cho
    Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.
  • Sujeong Eom
    Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, South Korea.
  • Daehoon Kim
    Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea.
  • Tae-Hoon Kim
    Interaction Laboratory of Advanced Technology Research Center, Korea University of Technology and Education, Cheonan, Chungcheongnam-do 31253, Republic of Korea.
  • Jae-Sun Uhm
    Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Hui-Nam Pak
    Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Moon-Hyoung Lee
    Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Pil-Sung Yang
    Department of Cardiology, CHA Bundang Medical Center, CHA University, Seongnam, Republic of Korea.
  • Eunjung Lee
    Department of Computational Science and Engineering, Yonsei University, Seoul, Korea.
  • Zachi Itzhak Attia
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Paul Andrew Friedman
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Seng Chan You
    Department of Biomedical Informatics, Ajou University School of Medicine, Suwon, South Korea.
  • Hee Tae Yu
    Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea.
  • Boyoung Joung
    Division of Cardiology, Department of Internal Medicine, Severance Cardiovascular Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Republic of Korea. cby6908@yuhs.ac.