Emerging role of artificial intelligence in cardiac electrophysiology

Rajesh Kabra; Sharat Israni; Bharat Vijay; Chaitanya Baru; Raghuveer Mendu; Mark Fellman; Arun Sridhar; Pamela Mason; Jim W Cheung; Luigi DiBiase; Srijoy Mahapatra; Jerome Kalifa; Steven A Lubitz; Peter A Noseworthy; Rachita Navara; David D McManus; Mitchell Cohen; Mina K Chung; Natalia Trayanova; Rakesh Gopinathannair; Dhanunjaya Lakkireddy

doi:10.1016/j.cvdhj.2022.09.001

Emerging role of artificial intelligence in cardiac electrophysiology

Cardiovasc Digit Health J. 2022 Sep 27;3(6):263-275. doi: 10.1016/j.cvdhj.2022.09.001. eCollection 2022 Dec.

Authors

Rajesh Kabra¹, Sharat Israni², Bharat Vijay³, Chaitanya Baru⁴, Raghuveer Mendu⁵, Mark Fellman⁶, Arun Sridhar⁷, Pamela Mason⁸, Jim W Cheung⁹, Luigi DiBiase¹⁰, Srijoy Mahapatra¹¹, Jerome Kalifa¹², Steven A Lubitz¹³, Peter A Noseworthy¹⁴, Rachita Navara¹⁵, David D McManus¹⁶, Mitchell Cohen¹⁷, Mina K Chung¹⁸, Natalia Trayanova¹⁹, Rakesh Gopinathannair¹, Dhanunjaya Lakkireddy¹

Affiliations

¹ Kansas City Heart Rhythm Institute, Kansas City, Kansas.
² Bakar Computational Health Sciences Institute, University of California, San Francisco, California.
³ AmberTag Inc, Milpitas, California.
⁴ San Diego Supercomputer Center, University of California, San Diego, San Diego, California.
⁵ NeuCures Inc, Los Angeles, California.
⁶ Fellman Device Group LLC, Rockville, Maryland.
⁷ University of Washington, Seattle, Washington.
⁸ Department of Medicine, University of Virginia, Charlottesville, Virginia.
⁹ Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, New York.
¹⁰ Albert Einstein College of Medicine at Montefiore Hospital, New York, New York.
¹¹ Department of Medicine, University of Minnesota, Minneapolis, Minnesota.
¹² Department of Cardiology, Brown University, Providence, Rhode Island.
¹³ Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, Massachusetts.
¹⁴ Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota.
¹⁵ Division of Cardiac Electrophysiology, University of California, San Francisco, San Francisco, California.
¹⁶ Department of Medicine, University of Massachusetts Chan Medical School, Worcester, Massachusetts.
¹⁷ Division of Pediatric Cardiology, INOVA Children's Hospital, Fairfax, Virginia.
¹⁸ Division of Cardiovascular Medicine, Cleveland Clinic, Cleveland, Ohio.
¹⁹ Department of Biomedical Engineering and Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland.

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.

Keywords: Artificial intelligence; Big data; Cardiac electrophysiology; Computational modeling; Deep learning; Machine learning.

Publication types

Review

Abstract

Publication types

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