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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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2025-07-01
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Series: | Frontiers in Public Health |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2025.1602566/full |
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