Tandem deep learning and logistic regression models to optimize hypertrophic cardiomyopathy detection in routine clinical practice

An electrocardiogram (ECG)-based artificial intelligence (AI) algorithm has shown good performance in detecting hypertrophic cardiomyopathy (HCM). However, its application in routine clinical practice may be challenging due to the low disease prevalence and potentially high false-positive rates. This study was conducted to identify clinical characteristics associated with true and false positive HCM AI-ECG results to improve its clinical application.