Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a mach...
Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach
About this item
Full title
Author / Creator
Publisher
London: Nature Publishing Group UK
Journal title
Language
English
Formats
Publication information
Publisher
London: Nature Publishing Group UK
Subjects
More information
Scope and Contents
Contents
Disparities in premature cardiovascular mortality (PCVM) have been associated with socioeconomic, behavioral, and environmental risk factors. Understanding the “phenotypes”, or combinations of characteristics associated with the highest risk of PCVM, and the geographic distributions of these phenotypes is critical to targeting PCVM interventions. T...
Alternative Titles
Full title
Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach
Authors, Artists and Contributors
Identifiers
Primary Identifiers
Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_e4ef3dfb82704d51a0052b7cdc55df7e
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e4ef3dfb82704d51a0052b7cdc55df7e
Other Identifiers
ISSN
2045-2322
E-ISSN
2045-2322
DOI
10.1038/s41598-023-30188-9
