Multicenter validation of AI-enabled ECG for pediatric biological sex prediction
Biological sex is closely linked to patterns embedded within the electrocardiogram (ECG) with essential health and disease implications. We report multicenter verification of an AI-enabled ECG model to predict biological sex across pediatric development. A previously published Mayo Clinic model confirmed puberty-linked AUROC gradient during external validation at Texas Children's Hospital (pre-puberty AUROC 0.64, peri-puberty AUROC 0.84, post-puberty AUROC 0.94). This phenomenon was replicated at Boston Children's Hospital. Saliency mapping revealed established sex-related electrophysiologic patterns.
Authors
- Jennifer Dugan (ORCID: https://orcid.org/0000-0002-1483-3201)
- Donnchadh O’Sullivan (ORCID: https://orcid.org/0000-0002-9492-8576)
- Scott Anjewierden (ORCID: https://orcid.org/0000-0001-5542-1599)
- Joshua Mayourian (ORCID: https://orcid.org/0000-0002-2364-1260)
- Stephen Morris (ORCID: https://orcid.org/0000-0002-6628-5809)
- Santiago O. Valdés
- Zachi Itzhak Attia
- Jeffrey J. Kim
- Malini Madhavan
- Kan Liu
- Tam T. Doan
- John K. Triedman
- Francisco Lopez-Jimenez
- Lance Patterson
- Talha Niaz
- Paul A. Friedman
- Daniel J. Penny
- Jonathan N. Johnson
Institutions
- Boston Children's Hospital (US)
- Harvard University (US)
- Mayo Clinic in Arizona (US)
- Texas Children's Hospital (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2026-02-26
- DOI
- https://doi.org/10.1038/s41746-026-02416-9
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00