Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy

摘要

AimsWe tested the hypothesis that a machine learning (ML) algorithm utilizing both complex echocardiographic data and clinical parameters could be used to phenogroup a heart failure (HF) cohort and identify patients with beneficial response to cardiac resynchronization therapy (CRT).