Machine Learning Approach Based on Echocardiographic Data to Improve Prediction of Cardiovascular Events in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy is a pathology with a highly variable course, ranging from patients who are asymptomatic throughout their lives to those who experience sudden death and/or terminal heart failure. The main objective is to develop and validate an algorithm (constructed through supervised learning) using cardiac imaging data to predict the risk of cardiovascular events in sarcomeric hypertrophic cardiomyopathy.