Deep Learning Algorithm Predicts Angiographic Coronary Artery Disease in Stable Patients Using Only a Standard 12-Lead Electrocardiogram.

Journal: The Canadian journal of cardiology
Published Date: Nov 1, 2021

Abstract

BACKGROUND: Current electrocardiogram analysis algorithms cannot predict the presence of coronary artery disease (CAD), especially in stable patients. This study assessed the ability of an artificial intelligence algorithm (ECGio; HEARTio Inc, Pittsburgh, PA) to predict the presence, location, and severity of coronary artery lesions in an unselected stable patient population.

Authors

  • Michael Leasure
    Heart Input Output Inc, DBA HEARTio, Pittsburgh, Pennsylvania, USA.
  • Utkars Jain
    Heart Input Output Inc, DBA HEARTio, Pittsburgh, Pennsylvania, USA.
  • Adam Butchy
    Heart Input Output Inc, DBA HEARTio, Pittsburgh, Pennsylvania, USA.
  • Jeremy Otten
    Department of Biomedical Engineering and Health Sciences, Drexel University, Philadelphia, Pennsylvania, USA.
  • Veronica A Covalesky
    Cardiology Consultants of Philadelphia, Philadelphia, Pennsylvania, USA; Jefferson University Hospital, Philadelphia, Pennsylvania, USA. Electronic address: VeronicaC@ccpdocs.com.
  • Daniel McCormick
    Cardiology Consultants of Philadelphia, Philadelphia, Pennsylvania, USA; Jefferson University Hospital, Philadelphia, Pennsylvania, USA.
  • Gary S Mintz
    Clinical Trial Center, Cardiovascular Research Foundation, New York, New York, USA.

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