Cargando…
Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach
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 phenoty...
Autores principales: | Dong, Weichuan, Motairek, Issam, Nasir, Khurram, Chen, Zhuo, Kim, Uriel, Khalifa, Yassin, Freedman, Darcy, Griggs, Stephanie, Rajagopalan, Sanjay, Al-Kindi, Sadeer G. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941082/ https://www.ncbi.nlm.nih.gov/pubmed/36808141 http://dx.doi.org/10.1038/s41598-023-30188-9 |
Ejemplares similares
-
Author Correction: Risk factors and geographic disparities in premature cardiovascular mortality in US counties: a machine learning approach
por: Dong, Weichuan, et al.
Publicado: (2023) -
Built Environment Features Obtained from Google Street View Are Associated with Coronary Artery Disease Prevalence: A Deep-Learning Framework
por: Chen, Zhuo, et al.
Publicado: (2023) -
Association Between Historical Neighborhood Redlining and Cardiovascular Outcomes Among US Veterans With Atherosclerotic Cardiovascular Diseases
por: Deo, Salil V., et al.
Publicado: (2023) -
Social Vulnerability and Excess Mortality in the COVID-19 Era
por: Motairek, Issam, et al.
Publicado: (2022) -
Excess Global Blood Pressure Associated With Fine Particulate Matter Air Pollution Levels Exceeding World Health Organization Guidelines
por: Brook, Robert D., et al.
Publicado: (2023)