Deep-Learning Models for the Echocardiographic Assessment of Diastolic Dysfunction

The authors explored a deep neural network (DeepNN) model that integrates multidimensional echocardiographic data to identify distinct patient subgroups with heart failure with preserved ejection fraction (HFpEF).The clinical algorithms for phenotyping the severity of diastolic dysfunction in HFpEF remain imprecise.The authors developed a DeepNN model to predict high- and low-risk phenogroups in a derivation cohort (n = 1,242). Model performance...