Why the study?
Do machine learning methods improve prognostication and identify clinically distinct phenotypes with heterogeneous responses to therapy in heart failure patients?
Population
Large cohort of heart failure (HF) patients
Design
Cohort
Authors
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Observational HF clusters should not alter care now; leaves open validation of therapeutic heterogeneity in prospective trials.
Do machine learning methods improve prognostication and identify clinically distinct phenotypes with heterogeneous responses to therapy in heart failure patients?
Machine learning and cluster analysis can identify distinct heart failure phenotypes with differing outcomes and therapeutic responses, potentially transforming future clinical trials.
Ahmad et al. (2018) studied this question.