Using Artificial Intelligence to Diagnose and Predict Outcomes in Hypertrophic Cardiomyopathy A Multicenter Study

What this Trial Is About

Researchers are studying hypertrophic cardiomyopathy HCM, a condition where the heart muscle thickens, making it harder to pump blood. This study aims to improve diagnosis and prognosis of HCM by using artificial intelligence AI to analyze the standard 12-lead electrocardiogram ECG. The project seeks to accurately classify different types of HCM and distinguish it from similar heart conditions like hypertensive heart disease and aortic stenosis, addressing challenges of late detection and inconsistent results across centers. The study uses AI models developed from a large historical dataset from multiple centers. These models analyze ECG signals to differentiate HCM from other heart conditions and healthy hearts. The approach combines deep learning with attention mechanisms and includes safeguards like version control, cloud-edge deployment, and offline replay evaluation to ensure reliable, real-world clinical use. The study involves three participant groups those diagnosed with HCM, those with left ventricular hypertrophy from other causes, and healthy individuals without heart thickening. Participants will be adults aged 18 or older divided into these groups based on heart imaging and history. Researchers will collect and analyze ECG data to evaluate the AI models diagnostic accuracy and generalizability over two years. The study does not involve treatment but focuses on observation and data collection. Participants heart health will be assessed through echocardiography and ECG, with data securely managed to support model development and validation until the study ends in 2026.

AI-Enabled Diagnosis and Prognosis of Hypertrophic Cardiomyopathy