Identification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram

Identification of cardiac wall motion abnormalities in diverse populations by deep learning of the electrocardiogram

Abstract Cardiac wall motion abnormalities (WMA) are strong predictors of mortality, but current screening methods using Q waves from electrocardiograms (ECGs) have limited accuracy and vary across racial and ethnic groups. This study aimed to identify novel ECG features using deep learning to enhan...

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Main Authors: Albert J. Rogers, Neal K. Bhatia, Sabyasachi Bandyopadhyay, James Tooley, Rayan Ansari, Vyom Thakkar, Justin Xu, Jessica Torres Soto, Jagteshwar S. Tung, Mahmood I. Alhusseini, Paul Clopton, Reza Sameni, Gari D. Clifford, J. Weston Hughes, Euan A. Ashley, Marco V. Perez, Matei Zaharia, Sanjiv M. Narayan
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:npj Digital Medicine
Online Access:https://doi.org/10.1038/s41746-024-01407-y
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https://doi.org/10.1038/s41746-024-01407-y

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