Personalized Heart Disease Detection via Generative Modeling of Anomalous ECG Digital Twins

A novel prospective learning approach that generates personalized ECG digital twins to simulate heart disease symptoms, enhancing the sensitivity of heart disease detection models to individual patient characteristics.