Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province

Interpretable machine learning analysis of environmental characteristics on bacillary dysentery in Sichuan Province

BackgroundBacterial dysentery (BD) is a leading cause of diarrhea-related mortality globally, with its incidence heavily influenced by environmental factors. However, a climate zone-specific predictive model for BD was currently lacking in Sichuan Province.ObjectiveThis study aims to employ interpre...

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Bibliographic Details
Main Authors: Yao Zhang, Qiao-Lin Wang, Wei Peng, Meng-Yuan Zhang, Yao Qin, Lun Zhang, Rong-Jie Wei, Dian-Ju Kang
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Public Health
Subjects:
bacterial dysentery
climate zones
environmental characteristics
XGBoost
SHAP
Online Access:https://www.frontiersin.org/articles/10.3389/fpubh.2025.1598247/full
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https://www.frontiersin.org/articles/10.3389/fpubh.2025.1598247/full

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