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 GopinathannairDhanunjaya Lakkireddy

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish (US)
Pages (from-to)263-275
Number of pages13
JournalCardiovascular Digital Health Journal
Volume3
Issue number6
DOIs
StatePublished - Dec 2022

Keywords

  • Artificial intelligence
  • Big data
  • Cardiac electrophysiology
  • Computational modeling
  • Deep learning
  • Machine learning

ASJC Scopus subject areas

  • Biomedical Engineering
  • Critical Care and Intensive Care Medicine
  • Cardiology and Cardiovascular Medicine

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