XGBoost model on county SDOH data predicts overdose mortality with top factors disability, hypertension, smoking and vehicle access; treatment deserts show 52.6% higher rates and 143 silent-risk counties are identified via clustering.
JAMA Network Open2(2), 190040 (2019) https://doi
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Social Determinants of Health and Fentanyl Overdose Mortality Across US Counties: An XGBoost and SHAP Analysis Identifying Silent Risk Counties and Treatment Deserts
XGBoost model on county SDOH data predicts overdose mortality with top factors disability, hypertension, smoking and vehicle access; treatment deserts show 52.6% higher rates and 143 silent-risk counties are identified via clustering.