Artificial Intelligence–Enabled ECG for Early Detection of Structural Heart Disease: Clinical Evidence, Applications, and Limitations
Artificial Intelligence–Enabled ECG for Early Detection of Structural Heart Disease: Clinical Evidence, Applications, and Limitations Introduction Cardiovascular disease remains the leading cause of mortality worldwide, accounting for nearly 20 million deaths annually. A major contributor to this burden is structural heart disease (SHD) —including left ventricular systolic dysfunction (LVSD), hypertrophic cardiomyopathy, valvular disease, and cardiomyopathies—which often progresses silently before symptoms emerge. Traditional diagnostic pathways rely heavily on imaging modalities such as echocardiography and cardiac MRI. While effective, these tools are resource-intensive and not scalable for population-wide screening. In contrast, the electrocardiogram (ECG) is inexpensive, ubiquitous, and standardized globally. Recent advances in artificial intelligence (AI)—particularly deep learning—have transformed the ECG from a simple electrical tracing into a high-dimensional predictive b...