Development and multicentre validation of an artificial intelligence electrocardiogram model for ventricular remodeling in repaired tetralogy of Fallot

European Heart Journal - Digital Health 2026 Open access

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Authors: S. Duong, Akhil Vaid, Pengfei Jiang, Yuval Bitterman, Yamini Krishnamurthy, I-Min Chiu, Joshua Finer, Brian Cleary, Benjamin S Glicksberg, Ruchira Garg, Michael P. DiLorenzo, Mark K. Friedberg
+12 more Evan M. Zahn, Matthew Lewis, Michael Satzer, David W. Ouyang, Pierre Elias, Tal Geva, Sunil J. Ghelani, Brett R. Anderson, Ali Zaidi, Rachel M. Wald, Girish N Nadkarni, Joshua Mayourian
DOI: 10.1093/ehjdh/ztag015
Cited by: 2
References: 44

Abstract

Aims: Periodic cardiac MRI (CMR) is recommended to identify adverse ventricular remodelling in repaired tetralogy of Fallot (TOF), but access to CMR is uneven, and compliance is poor. We developed a 12-lead electrocardiogram (ECG) artificial intelligence (AI) biomarker to identify CMR-quantified adverse biventricular remodelling in repaired TOF. Methods and results: , RV ejection fraction (EF)

Fields of Study & Subjects

Congenital Heart Disease Studies Congenital heart defects research Cardiac Arrhythmias and Treatments

Publication details

Journal / source
European Heart Journal - Digital Health
Publisher
Oxford University Press (OUP)
Volume
7
Issue
2
Pages
ztag015–ztag015
Publication date
27 January 2026
Language
EN