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Machine learning identifies prominent factors associated with cardiovascular disease: findings from two million adults in the Kashgar Prospective Cohort Study (KPCS)
BACKGROUND: Identifying factors associated with cardiovascular disease (CVD) is critical for its prevention, but this topic is scarcely investigated in Kashgar prefecture, Xinjiang, northwestern China. We thus explored the CVD epidemiology and identified prominent factors associated with CVD in this...
Autores principales: | Li, Jia-Xin, Li, Li, Zhong, Xuemei, Fan, Shu-Jun, Cen, Tao, Wang, Jianquan, He, Chuanjiang, Zhang, Zhoubin, Luo, Ya-Na, Liu, Xiao-Xuan, Hu, Li-Xin, Zhang, Yi-Dan, Qiu, Hui-Ling, Dong, Guang-Hui, Zou, Xiao-Guang, Yang, Bo-Yi |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9724436/ https://www.ncbi.nlm.nih.gov/pubmed/36474302 http://dx.doi.org/10.1186/s41256-022-00282-y |
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