Developing an interpretable machine learning predictive model of chronic obstructive pulmonary disease by serum PFAS concentration

Developing an interpretable machine learning predictive model of chronic obstructive pulmonary disease by serum PFAS concentration

BackgroundChronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide, with limited early detection strategies. While previous studies have examined the relationship between per- and polyfluoroalkyl substances (PFAS) and COPD, limited research has applied int...

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Bibliographic Details
Main Authors: Xiaomei Shao, Ling Zhang, Yuting Wang, Youmei Ying, Xueqin Chen
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Public Health
Subjects:
chronic obstructive pulmonary disease
machine learning
partial dependence plot
SHapley additive exPlanations
environment pollution
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2025.1602566/full
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