Behind the Science: ECG Prediction of Stroke | JACC

In this episode of Behind the Science, Adith Arun is joined by Drs. Rahul Mahajan and Shaan Khurshid to discuss their recent JACC study on using artificial intelligence–enabled electrocardiograms (ECGs) to predict long-term stroke risk. Drawing on data from over 200,000 patients, the team demonstrates how a single 12‑lead ECG can be leveraged to stratify stroke risk over 1-, 5-, and 10-year time horizons, achieving performance comparable to established clinical risk scores such as the Framingham Risk Score. The conversation explores key findings, including the model's association with cardioembolic stroke, insights from ECG signal interpretation (notably P‑wave features), and the potential role of ECG-based AI as both a scalable clinical tool and a novel biomarker for atrial cardiomyopathy. Tune in to learn how emerging AI technologies may transform stroke prevention, risk stratification, and future cardiovascular research. #Cardiology #StrokePrevention #ECG #ArtificialIntelligence #MedicalResearch #ACC #JACC