County-level phenomapping to identify disparities in cardiovascular outcomes: An unsupervised clustering analysis: Short title: Unsupervised clustering of counties and risk of cardiovascular mortality.

Journal: American journal of preventive cardiology
Published Date: Nov 20, 2020

Abstract

INTRODUCTION: Significant heterogeneity in cardiovascular disease (CVD) risk and healthcare resource allocation has been demonstrated in the United States, but optimal methods to capture heterogeneity in county-level characteristics that contribute to CVD mortality differences are unclear. We evaluated the feasibility of unsupervised machine learning (ML)-based phenomapping in identifying subgroups of county-level social and demographic risk factors with differential CVD outcomes.

Authors

  • Matthew W Segar
    Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Shreya Rao
    Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Ann Marie Navar
    Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Erin D Michos
    Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
  • Alana Lewis
    Department of Preventive Medicine, Northwestern University, Chicago, IL, USA.
  • Adolfo Correa
    Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
  • Mario Sims
    Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA.
  • Amit Khera
    Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Amy E Hughes
    Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, USA.
  • Ambarish Pandey
    Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA.

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