Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

Journal: PloS one
Published Date: Jul 9, 2025

Abstract

BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation and treatment response. Identifying distinct subphenotypes of HTN may improve our understanding of its underlying mechanisms and guide more precise treatment or public health initiatives.

Authors

  • Jaclyn M Hall
    Department of Health Outcomes & Biomedical Informatics, University of Florida, Gainesville, Florida, United States of America.
  • Jie Xu
    Second Affiliated Hospital Zhejiang University School of Medicine, Hangzhou, Zhejiang Province 310000, China.
  • Marta G Walsh
    Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, Florida, United States of America.
  • Hee-Deok Cho
    Department of Health Outcomes & Biomedical Informatics, University of Florida, Gainesville, Florida, United States of America.
  • Grant Harrell
    Department of Community Health & Family Medicine, University of Florida, Gainesville, Florida, United States of America.
  • Shailina A Keshwani
    Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, Florida, United States of America.
  • Steven M Smith
    Department of Pharmaceutical Outcomes & Policy, University of Florida, Gainesville, Florida, United States of America.
  • Stephanie A S Staras
    Department of Health Outcomes & Biomedical Informatics, University of Florida, Gainesville, Florida, United States of America.

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