Artificial Intelligence-Augmented Electrocardiogram Detection of Left Ventricular Systolic Dysfunction in the General Population.

Journal: Mayo Clinic proceedings
PMID: 34120755

Abstract

OBJECTIVE: To validate an artificial intelligence-augmented electrocardiogram (AI-ECG) algorithm for the detection of preclinical left ventricular systolic dysfunction (LVSD) in a large community-based cohort.

Authors

  • Anthony H Kashou
    Department of Medicine, Mayo Clinic, Rochester, Minnesota.
  • Jose R Medina-Inojosa
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
  • Peter A Noseworthy
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota.
  • Richard J Rodeheffer
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
  • Francisco Lopez-Jimenez
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • Itzhak Zachi Attia
    Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Suraj Kapa
    Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.
  • Christopher G Scott
    Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Alexander T Lee
    Division of Biostatistics, Mayo Clinic, Rochester, MN.
  • Paul A Friedman
    Department of Cardiovascular Medicine, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Paul M McKie
    Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA.

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