Artificial Intelligence for Cardiovascular Care-Part 1: Advances: JACC Review Topic of the Week.

Journal: Journal of the American College of Cardiology
Published Date: Apr 7, 2024

Abstract

Recent artificial intelligence (AI) advancements in cardiovascular care offer potential enhancements in diagnosis, treatment, and outcomes. Innovations to date focus on automating measurements, enhancing image quality, and detecting diseases using novel methods. Applications span wearables, electrocardiograms, echocardiography, angiography, genetics, and more. AI models detect diseases from electrocardiograms at accuracy not previously achieved by technology or human experts, including reduced ejection fraction, valvular heart disease, and other cardiomyopathies. However, AI's unique characteristics necessitate rigorous validation by addressing training methods, real-world efficacy, equity concerns, and long-term reliability. Despite an exponentially growing number of studies in cardiovascular AI, trials showing improvement in outcomes remain lacking. A number are currently underway. Embracing this rapidly evolving technology while setting a high evaluation benchmark will be crucial for cardiology to leverage AI to enhance patient care and the provider experience.

Authors

  • Pierre Elias
    Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY.
  • Sneha S Jain
    Division of Cardiology, Stanford University School of Medicine, Palo Alto, California, USA.
  • Timothy Poterucha
    Seymour, Paul and Gloria Milstein Division of Cardiology, Columbia University Irving Medical Center, New York, New York, USA.
  • Michael Randazzo
    University of Chicago Medical Center, Chicago, Illinois.
  • Francisco Lopez Jimenez
    Department of Cardiology, Mayo Clinic College of Medicine, Rochester, Minnesota, USA.
  • Rohan Khera
    Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.
  • Marco Perez
    Division of Cardiology, Stanford University, Palo Alto, CA, USA.
  • David Ouyang
    Division of Artificial Intelligence, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, California, USA.
  • James Pirruccello
    Division of Cardiology, University of California-San Francisco, San Francisco, California, USA.
  • Michael Salerno
    Department of Medicine, University of Virginia, Charlottesville, VA, USA.
  • Andrew J Einstein
    Division of Cardiology, Department of Medicine, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York; Department of Radiology, Columbia University Medical Center and New York-Presbyterian Hospital, New York, New York.
  • Robert Avram
    Division of Cardiology, Department of Medicine, Montreal Heart Institute, University of Montreal, Montreal, QC H1T 1C8, Canada. Electronic address: robert.avram.md@gmail.com.
  • Geoffrey H Tison
    Department of Medicine (G.H.T., M.H.L., E.F., M.A.A., C.J., K.E.F., R.C.D.).
  • Girish Nadkarni
    Division of Data-Driven and Digital Medicine (D3M), The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Vivek Natarajan
    Google, Mountain View, CA, USA.
  • Emma Pierson
    Department of Computer Science, Stanford University, Stanford, CA, USA.
  • Ashley Beecy
    Division of Cardiology, Department of Medicine, Weill Cornell Medicine and NewYork-Presbyterian, New York, NY, USA.
  • Deepa Kumaraiah
    Seymour, Paul, and Gloria Milstein Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center and NewYork-Presbyterian Hospital, New York, New York, USA.
  • Chris Haggerty
    Department of Biomedical Informatics Columbia University Irving Medical Center, New York, New York, USA; NewYork-Presbyterian Health System, New York, New York, USA.
  • Jennifer N Avari Silva
    Division of Cardiology, Washington University School of Medicine, St Louis, Missouri, USA.
  • Thomas M Maddox
    From the VA Eastern Colorado Healthcare System, Cardiology Section, University of Colorado School of Medicine, Colorado Cardiovascular Outcomes Research (CCOR) Consortium, Denver (T.M.M.); and VA Tennessee Valley Healthcare System, Medicine Department, Department of Biomedical Informatics, Medicine, and Biostatistics, Vanderbilt University, Nashville (M.A.M.). thomas.maddox@va.gov.

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