Opioid Overdose Death Prediction Using Machine Learning and Risk Factor Analysis Using SHAP Values for US Counties
Authors:
- 15 October 2025
- journal article
- research article
- Published by Springer Nature in International Journal of Mental Health and Addiction
- Vol. 24 (2) , 1865-1882
Abstract
No abstract availableKeywords
This publication has 24 references indexed in Scilit:
- Availability of Medications for Opioid Use Disorder in Community Mental Health FacilitiesJAMA Network Open, 2024
- Estimating Weekly National Opioid Overdose Deaths in Near Real Time Using Multiple Proxy Data SourcesJAMA Network Open, 2022
- Trends in opioid-related crime incidents and comparison with opioid overdose outcomes in the United StatesInternational Journal of Drug Policy, 2022
- What makes a good prediction? Feature importance and beginning to open the black box of machine learning in geneticsHuman Genetics, 2021
- Identifying counties at risk of high overdose mortality burden during the emerging fentanyl epidemic in the USA: a predictive statistical modelling studyThe Lancet Public Health, 2021
- Predicting opioid overdose risk of patients with opioid prescriptions using electronic health records based on temporal deep learningJournal of Biomedical Informatics, 2021
- Machine learning for phenotyping opioid overdose eventsJournal of Biomedical Informatics, 2019
- Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid PrescriptionsJAMA Network Open, 2019
- Trends and Patterns of Geographic Variation in Opioid Prescribing Practices by State, United States, 2006-2017JAMA Network Open, 2019
- Urban vs. rural differences in prescription opioid misuse among adults in the United States: Informing region specific drug policies and interventionsInternational Journal of Drug Policy, 2015