Cargando…
Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study
BACKGROUND: Little is known about whether machine-learning algorithms developed to predict opioid overdose using earlier years and from a single state will perform as well when applied to other populations. We aimed to develop a machine-learning algorithm to predict 3-month risk of opioid overdose u...
Autores principales: | Lo-Ciganic, Wei-Hsuan, Donohue, Julie M, Yang, Qingnan, Huang, James L, Chang, Ching-Yuan, Weiss, Jeremy C, Guo, Jingchuan, Zhang, Hao H, Cochran, Gerald, Gordon, Adam J, Malone, Daniel C, Kwoh, Chian K, Wilson, Debbie L, Kuza, Courtney C, Gellad, Walid F |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9236281/ https://www.ncbi.nlm.nih.gov/pubmed/35623798 http://dx.doi.org/10.1016/S2589-7500(22)00062-0 |
Ejemplares similares
-
Evaluation of Machine-Learning Algorithms for Predicting Opioid Overdose Risk Among Medicare Beneficiaries With Opioid Prescriptions
por: Lo-Ciganic, Wei-Hsuan, et al.
Publicado: (2019) -
Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: A machine-learning approach
por: Lo-Ciganic, Wei-Hsuan, et al.
Publicado: (2021) -
Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: A prognostic study
por: Lo-Ciganic, Wei-Hsuan, et al.
Publicado: (2020) -
Prescription Opioid Quality Measures Applied Among Pennsylvania Medicaid Enrollees
por: Cochran, Gerald, et al.
Publicado: (2018) -
Medicaid expansion and opioid supply policies to address the opioid overdose crisis
por: Shakya, Shishir, et al.
Publicado: (2022)