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

Yan-bin Wu; Shu-xiang Deng

doi:10.1117/12.2682554

20 June 2023 Main heavy metals affecting chronic kidney disease: a study based on feature selection algorithm

Yan-bin Wu, Shu-xiang Deng

Proceedings Volume 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023); 127150M (2023) https://doi.org/10.1117/12.2682554
Event: Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 2023, Dalian, China

Abstract

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 metals and quartiles of different population risk subgroups to validate the feature selection results. We found that the selected blood lead and urinary cadmium had a strong effect to CKD and the results were statistically significant. the method based on SHAP and XGBoost could discover the possible causal factors in vivo.

Citation Download Citation

Yan-bin Wu and Shu-xiang Deng "Main heavy metals affecting chronic kidney disease: a study based on feature selection algorithm", Proc. SPIE 12715, Eighth International Conference on Electronic Technology and Information Science (ICETIS 2023), 127150M (20 June 2023); https://doi.org/10.1117/12.2682554

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