可解释性
类风湿性关节炎
鉴定(生物学)
Lasso(编程语言)
医学
全国健康与营养检查调查
机器学习
骨关节炎
人工智能
计算机科学
物理疗法
数据科学
环境卫生
替代医学
内科学
病理
人口
植物
万维网
生物
作者
Wenxuan Fan,Zhipeng Pi,Keyu Kong,Hua Qiao,Minghao Jin,Yongyun Chang,Jingwei Zhang,Huiwu Li
标识
DOI:10.3389/fnut.2024.1422617
摘要
This investigation leverages advanced machine learning (ML) techniques to dissect the complex relationship between heavy metal exposure and its impacts on osteoarthritis (OA) and rheumatoid arthritis (RA). Utilizing a comprehensive dataset from the National Health and Nutrition Examination Survey (NHANES) spanning from 2003 to 2020, this study aims to elucidate the roles specific heavy metals play in the incidence and differentiation of OA and RA.
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