2024
DOI: 10.3389/fpubh.2023.1309490
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Can adverse childhood experiences predict chronic health conditions? Development of trauma-informed, explainable machine learning models

Hanin B. Afzal,
Tasfia Jahangir,
Yiyang Mei
et al.

Abstract: IntroductionDecades of research have established the association between adverse childhood experiences (ACEs) and adult onset of chronic diseases, influenced by health behaviors and social determinants of health (SDoH). Machine Learning (ML) is a powerful tool for computing these complex associations and accurately predicting chronic health conditions.MethodsUsing the 2021 Behavioral Risk Factor Surveillance Survey, we developed several ML models—random forest, logistic regression, support vector machine, Naïv… Show more

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