Spatio-temporal modeling of asthma-prone areas: Exploring the influence of urban climate factors with explainable artificial intelligence (XAI)

•Utilized XGBoost-BA for accurate spatio-temporal modeling of asthma-prone areas.•SHAP analysis revealed seasonal impacts of climate and air pollution on asthma.•Rainfall in spring/autumn and temperature in summer/winter were key factors.•High accuracy achieved in predicting asthma-prone areas acros...

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Veröffentlicht in:	Sustainable cities and society Jg. 116; S. 105889
Hauptverfasser:	Razavi-Termeh, Seyed Vahid, Sadeghi-Niaraki, Abolghasem, Ali, Farman, Naqvi, Rizwan Ali, Choi, Soo-Mi
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.12.2024
Schlagworte:	Asthma Explainable artificial intelligence (XAI) Healthy cities Spatio-temporal modeling Urban environmental factors Urban environmental factors Healthy cities Explainable artificial intelligence (XAI) Spatio-temporal modeling Asthma
ISSN:	2210-6707
Online-Zugang:	Volltext
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