January 7, 2020Open Access

Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning

Structured PICO

Population

Patients with heart failure with preserved ejection fraction (HFpEF)

Machine learning can identify distinct phenogroups in HFpEF with differing clinical outcomes and biomarker profiles, highlighting the heterogeneity of the disease.

Abstract

Using machine learning we identified distinct HFpEF phenogroups with differential characteristics and outcomes, as well as differential levels of inflammatory and cardiovascular proteins.

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Authors

Åsa K. Hedman

Pfizer (United States)

Camilla Hage

Heart Failure & Transplant

Anil Kumar Sharma

Chandigarh University

Journals

Heart

Actions

Institutions

Northwestern University

Karolinska Institutet

University of Gothenburg

References and Citations

Connected Papers

Building similarity graph...

Analyzing shared references across papers

Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning

Structured PICO

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

Cite this study

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