Detection of hypertrophic cardiomyopathy by an artificial intelligence electrocardiogram in children and adolescents.

Journal: International journal of cardiology
Published Date: Oct 1, 2021

Abstract

BACKGROUND: There is no established screening approach for hypertrophic cardiomyopathy (HCM). We recently developed an artificial intelligence (AI) model for the detection of HCM based on the 12‑lead electrocardiogram (AI-ECG) in adults. Here, we aimed to validate this approach of ECG-based HCM detection in pediatric patients (age ≤ 18 years).

Authors

  • Konstantinos C Siontis
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
  • Kan Liu
    Department of Urology, Hunan Cancer Hospital, Changsha, Hunan, China.
  • J Martijn Bos
    Department of Cardiovascular Medicine; Windland Smith Rice Sudden Death Genomics Laboratory, Department of Molecular Pharmacology and Experimental Therapeutics (J.M.B., M.J.A.), Mayo Clinic, Rochester, MN.
  • Zachi I Attia
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Michal Cohen-Shelly
    Department of Cardiovascular Medicine Mayo Clinic Rochester MN.
  • Adelaide M Arruda-Olson
    Mayo Clinic Rochester, MN.
  • Nasibeh Zanjirani Farahani
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, United States of America.
  • Paul A Friedman
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Peter A Noseworthy
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota.
  • Michael J Ackerman
    Department of Cardiovascular Medicine, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.

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