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

摘要

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.