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Predictive modeling the probability of suffering from metabolic syndrome using machine learning: A population-based study
BACKGROUND: There is an increasing trend of Metabolic syndrome (MetS) prevalence, which has been considered as an important contributor for cardiovascular disease (CVD), cancers and diabetes. However, there is often a long asymptomatic phase of MetS, resulting in not diagnosed and intervened so time...
Autores principales: | Hu, Xiang, Li, Xue-Ke, Wen, Shiping, Li, Xingyu, Zeng, Tian-Shu, Zhang, Jiao-Yue, Wang, Weiqing, Bi, Yufang, Zhang, Qiao, Tian, Sheng-Hua, Min, Jie, Wang, Ying, Liu, Geng, Huang, Hantao, Peng, Miaomiao, Zhang, Jun, Wu, Chaodong, Li, Yu-Ming, Sun, Hui, Ning, Guang, Chen, Lu-Lu |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9834713/ https://www.ncbi.nlm.nih.gov/pubmed/36643319 http://dx.doi.org/10.1016/j.heliyon.2022.e12343 |
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