Use of Electrocardiograms to Identify Coronary Artery Disease
This study demonstrated the clinical utility of a deep learning artificial intelligence algorithm to analyze a digital 12-lead ECG to predict the presence of clinically significant CAD as determined by coronary angiography.
Authors
- Veronica A. Covalesky
- Brent A. Williams (ORCID: https://orcid.org/0000-0002-7721-4483)
- Adam Butchy (ORCID: https://orcid.org/0000-0002-0096-0031)
- Michael Leasure (ORCID: https://orcid.org/0000-0002-1488-712X)
- Prahlad Menon
- GS Mintz
- Indu Poornima
- Utkars Jain
- Michael Warnick
- John Rehder
- Devin Vasoya
Institutions
- Allegheny Health Network (US)
- Thomas Jefferson University (US)
- University of Pittsburgh (US)
- Heart Foundation (US)
- Cardiovascular Research Foundation (US)
- Temple University (US)
Publication Details
- Journal
- JACC Advances
- Published
- 2026-01-29
- DOI
- https://doi.org/10.1016/j.jacadv.2025.102573
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00