Cardiovascular Digital Health Journal (Dec 2022)
Emerging role of artificial intelligence in cardiac electrophysiology
- Rajesh Kabra, MD, FHRS,
- Sharat Israni, PhD,
- Bharat Vijay, MS,
- Chaitanya Baru, PhD,
- Raghuveer Mendu, BTech,
- Mark Fellman, BS,
- Arun Sridhar, MD, FHRS,
- Pamela Mason, MD, FHRS,
- Jim W. Cheung, MD, FHRS,
- Luigi DiBiase, MD, PhD, FHRS,
- Srijoy Mahapatra, MD, FHRS,
- Jerome Kalifa, MD, PhD,
- Steven A. Lubitz, MD,
- Peter A. Noseworthy, MD, FHRS,
- Rachita Navara, MD,
- David D. McManus, MD, FHRS,
- Mitchell Cohen, MD,
- Mina K. Chung, MD, FHRS,
- Natalia Trayanova, PhD, FHRS,
- Rakesh Gopinathannair, MD, FHRS,
- Dhanunjaya Lakkireddy, MD, FHRS
Affiliations
- Rajesh Kabra, MD, FHRS
- Kansas City Heart Rhythm Institute, Kansas City, Kansas
- Sharat Israni, PhD
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California
- Bharat Vijay, MS
- AmberTag Inc, Milpitas, California
- Chaitanya Baru, PhD
- San Diego Supercomputer Center, University of California, San Diego, San Diego, California
- Raghuveer Mendu, BTech
- NeuCures Inc, Los Angeles, California
- Mark Fellman, BS
- Fellman Device Group LLC, Rockville, Maryland
- Arun Sridhar, MD, FHRS
- University of Washington, Seattle, Washington
- Pamela Mason, MD, FHRS
- Department of Medicine, University of Virginia, Charlottesville, Virginia
- Jim W. Cheung, MD, FHRS
- Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, New York
- Luigi DiBiase, MD, PhD, FHRS
- Albert Einstein College of Medicine at Montefiore Hospital, New York, New York
- Srijoy Mahapatra, MD, FHRS
- Department of Medicine, University of Minnesota, Minneapolis, Minnesota
- Jerome Kalifa, MD, PhD
- Department of Cardiology, Brown University, Providence, Rhode Island
- Steven A. Lubitz, MD
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, Massachusetts
- Peter A. Noseworthy, MD, FHRS
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota
- Rachita Navara, MD
- Division of Cardiac Electrophysiology, University of California, San Francisco, San Francisco, California
- David D. McManus, MD, FHRS
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts
- Mitchell Cohen, MD
- Division of Pediatric Cardiology, INOVA Children’s Hospital, Fairfax, Virginia
- Mina K. Chung, MD, FHRS
- Division of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio
- Natalia Trayanova, PhD, FHRS
- Department of Biomedical Engineering and Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland
- Rakesh Gopinathannair, MD, FHRS
- Kansas City Heart Rhythm Institute, Kansas City, Kansas
- Dhanunjaya Lakkireddy, MD, FHRS
- Kansas City Heart Rhythm Institute, Kansas City, Kansas; Address reprint requests and correspondence: Dr Dhanunjaya Lakkireddy, Kansas City Heart Rhythm Institute & Research Foundation, 5100 W. 110th St, Suite-200, Overland Park, KS 66211.
- Journal volume & issue
-
Vol. 3,
no. 6
pp. 263 – 275
Abstract
Artificial intelligence (AI) and machine learning (ML) have significantly impacted the field of cardiovascular medicine, especially cardiac electrophysiology (EP), on multiple fronts. The goal of this review is to familiarize readers with the field of AI and ML and their emerging role in EP. The current review is divided into 3 sections. In the first section, we discuss the definitions and basics of AI, ML, and big data. In the second section, we discuss their application to EP in the context of detection, prediction, and management of arrhythmias. Finally, we discuss the regulatory issues, challenges, and future directions of AI in EP.
