More than meets the eye: Using AI to identify reduced heart function by electrocardiograms
- PMID: 35590216
- DOI: 10.1016/j.medj.2021.06.003
More than meets the eye: Using AI to identify reduced heart function by electrocardiograms
Abstract
Electrocardiographic (ECG) assessment of patients with suspected heart disease is a bedrock of cardiology for diagnosing conduction system disease, arrhythmias, and heart attack. Now, using AI-assisted interpretation of ECGs, the signals within these studies are able to tell us so much more. In their recent randomized trial published in Nature Medicine, Yao and colleagues illustrate the power of utilizing AI-enabled ECGs to identify individuals with reduced heart function using a scalable, pragmatic approach.
Copyright © 2021 Elsevier Inc. All rights reserved.
Conflict of interest statement
Declaration of interests Scripps Research Translational Institute receives funding from Philips.
Comment on
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Artificial intelligence-enabled electrocardiograms for identification of patients with low ejection fraction: a pragmatic, randomized clinical trial.Nat Med. 2021 May;27(5):815-819. doi: 10.1038/s41591-021-01335-4. Epub 2021 May 6. Nat Med. 2021. PMID: 33958795 Clinical Trial.
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