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Cardiovascular diseases (CVDs) are the leading cause of morbidity and mortality worldwide.1 High systolic blood pressure (SBP) remains one of the top risk factors for CVD burden globally.2 Despite being a modifiable risk factor, hypertension (HTN) remains largely undiagnosed and untreated due to inadequate screening, poor awareness and lack of treatment adherence.3 Globally, HTN is undiagnosed in about 46% […]

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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