IDENTIFYING PHENOGROUPS IN PATIENTS WITH DIASTOLIC DYSFUNCTION USING CLUSTER ANALYSIS

Clinical factors that predispose patients with asymptomatic diastolic dysfunction (DD) to develop heart failure with preserved ejection fraction (HFpEF) are not well understood. We hypothesized that machine learning could identify clusters of patients with distinct phenotypes of DD, in which