March 2, 2021Open Access

Machine learning based on biomarker profiles identifies distinct subgroups of heart failure with preserved ejection fraction

Structured PICO

Does machine learning based on biomarker profiles identify distinct subgroups of patients with HFpEF?

Population

Patients with heart failure with preserved ejection fraction (HFpEF)

Intervention

Unsupervised cluster analysis (machine learning) based on biomarker profiles

Outcome

Identification of mutually exclusive subgroups with distinct biomarker profiles, clinical characteristics and outcomes

Machine learning based on biomarker profiles can identify distinct pathophysiological subgroups in patients with HFpEF.

Abstract

Unsupervised cluster analysis based on biomarker profiles identified mutually exclusive subgroups of patients with HFpEF with distinct biomarker profiles, clinical characteristics and outcomes, suggesting different underlying pathophysiological pathways.

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Cite This Study

Woolley et al. (Tue,) studied this question.

synapsesocial.com/papers/69effb6cafa91c76b5d0a89f https://doi.org/https://doi.org/10.1002/ejhf.2144

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