Interpretable machine learning insights into the association between PFAS exposure and diabetes mellitus

Interpretable machine learning insights into the association between PFAS exposure and diabetes mellitus

Background: Diabetes Mellitus (DM) is a global health concern with rising prevalence, and its link to PFAS exposure remains unclear. No machine learning (ML) models have yet been developed to predict DM based on PFAS exposure. Methods: We analyzed data from 10471 participants in National Health and...

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Bibliographic Details
Main Authors: Cui Wang, Xinping Xu, Shuai Luo, Man Luo, Sha Li, Jianhong Si
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Ecotoxicology and Environmental Safety
Subjects:
Diabetes Mellitus
Interpretable machine learning
Per- and polyfluoroalkyl substances
SHapley Additive exPlanations
Partial Dependence Analysis
Environmental pollution
Online Access:http://www.sciencedirect.com/science/article/pii/S0147651325009145
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