The relationship between heavy metals and metabolic syndrome using machine learning.

Journal: Frontiers in public health
PMID: 38686033

Abstract

BACKGROUND: Exposure to high levels of heavy metals has been widely recognized as an important risk factor for metabolic syndrome (MetS). The main purpose of this study is to assess the associations between the level of heavy metal exposure and Mets using machine learning (ML) method.

Authors

  • Jun Yao
    College of Chemistry and Chemical Engineering, Southwest Petroleum University, Chengdu 610500, People's Republic of China; State Key Laboratory of Oil & Gas Reservoir Geology and Exploitation, Southwest Petroleum University, Chengdu 610500, People's Republic of China. Electronic address: yjhwsgt@163.com.
  • Zhilin Du
    Department of Oncology, Chengdu Seventh People's Hospital (Affliated Cancer Hospital of Chengdu Medical College), Chengdu, Sichuan, China.
  • Fuyue Yang
    Department of Rheumatology and Immunology, Chengdu Fifth People's Hospital, Chengdu, Sichuan, China.
  • Ran Duan
    Clinical Medical College, Chengdu Medical College, Chengdu, Sichuan, China
  • Tong Feng
    Department of Biomedical Engineering, Tianjin University, 92 Weijin Rd., Tianjin, 300072, China.

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