Artificial Intelligence for the Detection of Hypertrophic Cardiomyopathy From Standard Electrocardiogram.

Jakob Park¹, Jonathan Kermanshahchi², Christopher J Love³, Klevin Roger Reyes⁴, Alexander Kukuev⁴, Sarit Meshesha³, Katia Kon³, Florian Rader⁵

¹Smidt Heart Institute, Department of Cardiology, Cedars-Sinai Medical Center, Los Angeles, California, USA. Electronic address: jakobpark0@gmail.com.

²California University of Science and Medicine, Colton, California, USA.

³Viz.ai Inc, San Francisco, California, USA.

⁴Smidt Heart Institute, Department of Cardiology, Cedars-Sinai Medical Center, Los Angeles, California, USA.

⁵Smidt Heart Institute, Department of Cardiology, Cedars-Sinai Medical Center, Los Angeles, California, USA. Electronic address: https://twitter.com/RaderFlorian.

PubMed PMC DOI PDF

Abstract

BACKGROUND: Hypertrophic cardiomyopathy (HCM) is often diagnosed late, increasing avoidable risk and delaying treatment. Artificial intelligence (AI) for 12-lead electrocardiograms (ECGs) may identify undetected HCM earlier. OBJECTIVES: This study aimed to evaluate the performance of an AI algorithm for HCM detection and identify predictors of correct classification. METHODS: Of 314 patients wit…

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