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...

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Detalles Bibliográficos
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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Research Article
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

Internet

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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