Artificial Intelligence in Cardiovascular Care-Part 2: Applications: 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 effective diagnosis, treatment, and outcomes. More than 600 U.S. Food and Drug Administration-approved clinical AI algorithms now exist, with 10% focusing on cardiovascular applications, highlighting the growing opportunities for AI to augment care. This review discusses the latest advancements in the field of AI, with a particular focus on the utilization of multimodal inputs and the field of generative AI. Further discussions in this review involve an approach to understanding the larger context in which AI-augmented care may exist, and include a discussion of the need for rigorous evaluation, appropriate infrastructure for deployment, ethics and equity assessments, regulatory oversight, and viable business cases for deployment. Embracing this rapidly evolving technology while setting an appropriately high evaluation benchmark with careful and patient-centered implementation will be crucial for cardiology to leverage AI to enhance patient care and the provider experience.

Authors

  • Sneha S Jain
    Division of Cardiology, Stanford University School of Medicine, Palo Alto, California, USA.
  • Pierre Elias
    Division of Cardiology, Department of Medicine, Columbia University Irving Medical Center, New York, NY.
  • 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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