Regression analysis of air pollution and pediatric respiratory diseases based on interpretable machine learning

Regression analysis of air pollution and pediatric respiratory diseases based on interpretable machine learning

Air pollution is of high relevance to human health. In this study, multiple machine-learning (ML) models—linear regression, random forest (RF), AdaBoost, and neural networks (NNs)—were used to explore the potential impacts of air-pollutant concentrations on the incidence of pediatric respiratory dis...

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Bibliographic Details
Main Authors: Yan Ji, Xiefei Zhi, Ying Wu, Yanqiu Zhang, Yitong Yang, Ting Peng, Luying Ji
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-03-01
Series:Frontiers in Earth Science
Subjects:
air pollutants
respiratory diseases in children
explainable artificial intelligence (XAI)
feature importance analysis
Taizhou city
Online Access:https://www.frontiersin.org/articles/10.3389/feart.2023.1105140/full

Internet

https://www.frontiersin.org/articles/10.3389/feart.2023.1105140/full

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