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Native valve infective endocarditis (IE) is rare, with an incidence of 3–7 cases per 100,000 person-years.1,2 Cardiac structural complications from local infection extension include valvular destruction, peri-annular abscess and fistula formation. Left ventricular pseudoaneurysm (LVP) from IE is exceedingly rare, occurring in <1% of cases, and is associated with high morbidity and mortality. Diagnosis is challenging due to nonspecific symptoms […]

Sanjiv Narayan, EHRA 2021 – AI and ML Models in Arrhythmias and Cardiac Electrophysiology

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Published Online: Jun 15th 2021

It was a pleasure to talk to Dr Sanjiv Narayan (Stanford University, Stanford, CA, USA) around the implementation of artificial intelligence and machine learning models in the field of arrhythmias and cardiac electrophysiology.

Questions

  1. What are the major challenges in implementing artificial intelligence (AI) and machine learning (ML) models in the field of arrhythmias and cardiac electrophysiology? (0:25)
  2. How has computer modelling helped us understand the mechanisms underlying cardiac arrhythmias? (3:23)
  3. What are the potential applications of AI and ML in the future of arrhythmia diagnosis, prognosis and management? (4:46)

Speaker disclosures: Dr. Narayan reports consulting from Beyond.ai Inc, TDK Inc., Up to Date, Abbott Laboratories, and American College of Cardiology Foundation; Intellectual Property Rights from University of California Regents and Stanford University

Interview and filming supported by Touch Medical Media.

Filmed during a remote video call with Dr Sanjiv Narayan as a highlight of EHRA 2021, April 2021.

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