The Lead Episode 119: A Discussion of Near-Term Prediction of Sustained Ventricular Arrythmias Applying Artificial Intelligence to Single-Lead Ambulatory Electrocardiogram LIVE at HRX

Discussion Topic: Near-Term Prediction of Sustained Ventricular Arrythmias Applying Artificial Intelligence to Single-Lead Ambulatory Electrocardiogram

Please join Digital Education Committee Vice-Chair, Tina Baykaner, MD, MPH, of Stanford University, as she is joined by Heart Rhythm Society President Mina K. Chung, MD, FHRS, of the Cleveland Clinic, and Konstantinos C. Siontis, MD, FHRS of the May Clinic. The three met up in Altanta at HRX 2025 for this stimulating coversation.

This study evaluated whether artificial intelligence applied to single-lead ambulatory ECGs could predict imminent sustained ventricular arrhythmias. Using deep learning models, the researchers demonstrated that AI could identify subtle ECG features preceding arrhythmic events, enabling accurate short-term risk prediction. The findings suggest a potential role for AI-enhanced ECG monitoring to improve early detection and prevention of life-threatening ventricular arrhythmias.

Host: Tina Baykaner, MD, MPH
Guests: Mina K. Chung, MD, FHRS and Konstantinos C. Siontis, MD, FHRS

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