Looking Beyond Rhythm: A New Role for the Pediatric ECG

The electrocardiogram (ECG) remains one of the most widely used diagnostic tools in pediatric cardiology and is integral to the comprehensive evaluation of a child. However, the ability for a clinician to truly understand all the physiologic patterns is infeasible. In addition, there are many age-related normal variations, and the complexity of congenital heart disease can make subtle abnormalities difficult to recognize, particularly outside pediatric specialty centers.

Researchers are now exploring whether artificial intelligence (AI) can identify clinically meaningful patterns hidden within a standard ECG, potentially helping clinicians recognize children who may benefit from earlier imaging, specialty evaluation or closer follow-up.

During the Cardiology 2026 conference, David M. Leone, MD, MS, cardiologist at Cincinnati Children's and founder of the Cincinnati Children's AI Collaborative, shared emerging research on how AI-enhanced ECG analysis could expand the diagnostic value of this test.

Research Suggests Broader Clinical Applications

A recent review co-authored by Dr. Leone evaluated 17 pediatric studies investigating AI-assisted ECG interpretation across a range of cardiovascular conditions.

Collectively, the studies found promising applications in:

• Congenital heart disease
• Left and right ventricular dysfunction
• Hypertrophic cardiomyopathy
• Concealed long QT syndrome
• Neonatal bradycardia
• Risk prediction for future cardiovascular events

Several studies demonstrated that AI models could identify ventricular dysfunction using a routine ECG, while others detected congenital heart disease that may not be readily apparent through conventional ECG interpretation. Although these findings require additional validation, they suggest AI could eventually help identify children who warrant earlier cardiac imaging or specialty referral, allowing for access of specialty care to areas where this may be limited.

What Needs to Happen Before Clinical Adoption

AI is not intended to replace pediatric cardiologists or traditional diagnostic evaluation. Instead, it has the potential to become a clinical decision-support tool that helps physicians identify children who may benefit from earlier imaging, additional testing or specialty referral.

While the early evidence is encouraging, AI-enhanced ECG interpretation is not ready for routine clinical use.

Researchers emphasize that broader adoption will require:

• Larger, more diverse pediatric datasets
• Prospective multicenter validation and study
• Explainable AI that supports physician decision-making
• Integration into existing clinical workflows
• Continued attention to patient privacy, bias and regulatory oversight

These steps will be essential to ensuring AI improves care while maintaining physician confidence and patient safety.

Cincinnati Children's is helping advance the research needed to responsibly translate that potential into clinical practice—with the goal of improving earlier diagnosis and better outcomes for children with cardiovascular disease.

(Published August 2026)

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