Machine learning and explainable artificial intelligence to predict and interpret lead toxicity in pregnant women and unborn baby

Machine learning and explainable artificial intelligence to predict and interpret lead toxicity in pregnant women and unborn baby

IntroductionLead toxicity is a well-recognised environmental health issue, with prenatal exposure posing significant risks to infants. One major pathway of exposure to infants is maternal lead transfer during pregnancy. Therefore, accurately characterising maternal lead levels is critical for enabli...

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Bibliographic Details
Main Authors: Priyanka Chaurasia, Pratheepan Yogarajah, Abbas Ali Mahdi, Sally McClean, Mohammad Kaleem Ahmad, Tabrez Jafar, Sanjay Kumar Singh
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-05-01
Series:Frontiers in Digital Health
Subjects:
machine learning
classification
predictive modelling
explainable AI
lead toxicity
Online Access:https://www.frontiersin.org/articles/10.3389/fdgth.2025.1608949/full
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https://www.frontiersin.org/articles/10.3389/fdgth.2025.1608949/full

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