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Ventricular fibrillation (VF) is characterized by rapid (>300 beats a per minute), irregular electrical activation with variable electrocardiographic waveforms that prevents coordinated myocardial contraction, resulting in immediate loss of cardiac output.1 It most commonly occurs in the context of coronary artery disease.2,3 Resuscitation efforts are critically time-dependent: with each minute of untreated VF, the survival rate declines […]

Sanjiv Narayan, EHRA 2021 – Applications of Computer Modelling and Machine Learning

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Published Online: Jun 15th 2021

We were delighted to talk to Dr Sanjiv Narayan (Stanford University, Stanford, CA, USA) around the applications of computer modelling and machine learning in the field of arrhythmias and cardiac electrophysiology.

Questions

  1. What are artificial intelligence or machine learning and how could they be used in cardiology? (0:25)
  2. Could you give us some examples of where computer modelling and machine learning (ML) have been successfully used in atrial fibrillation? (1:27)
  3. Could you give us some examples of where computer modelling and ML have been successfully used to prevent sudden death? (4:01)

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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