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Main heavy metals affecting chronic kidney disease: A study based on feature selection algorithm

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成果类型:
期刊论文
作者:
Wu, Yan-Bin;Deng, Shu-Xiang
通讯作者:
Wu, Yan-Bin(wuyanbin@stu.usc.edu.cn)
作者机构:
[Wu, Yan-Bin] College of Computer Science, University of South China, Hunan, Hengyang, China
[Deng, Shu-Xiang] School of Public Health, University of South China, Hunan, Hengyang, China
语种:
英文
期刊:
Proceedings of SPIE - The International Society for Optical Engineering
ISSN:
0277-786X
年:
2023
卷:
12715
页码:
119
机构署名:
本校为第一机构
院系归属:
公共卫生学院
摘要:
In recent years, the global prevalence of chronic kidney disease (CKD) has been increasing year by year, and heavy metals that are widely distributed in the environment are nephrotoxic, leading to possible kidney damage and affecting human health. Therefore, this study used laboratory heavy metal data from the National Health and Nutrition Examination Survey (NHANES) to select the main heavy metals that affect the kidney by fusing SHAP values and XGBoost algorithm of heavy metal selection method. Later, we combined Odds Ratio (OR) of heavy meta...

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