Predicting the risk of cardiovascular disease in adults exposed to heavy metals: Interpretable machine learning

Predicting the risk of cardiovascular disease in adults exposed to heavy metals: Interpretable machine learning

Machine learning exhibits excellent performance in terms of predictive power. We aimed to construct an interpretable machine learning model utilizing National Health and Nutrition Examination Survey data to investigate the relationship between heavy metal exposure and cardiovascular disease (CVD). A...

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Bibliographic Details
Main Authors: Meiyue Shen, Yine Zhang, Runqing Zhan, Tingwei Du, Peixuan Shen, Xiaochuan Lu, Shengnan Liu, Rongrong Guo, Xiaoli Shen
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Ecotoxicology and Environmental Safety
Subjects:
Cardiovascular disease
Heavy metals
Machine learning
Random forest
AdaBoost
Partial dependence plot
Online Access:http://www.sciencedirect.com/science/article/pii/S0147651324016464
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