Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study-Reference-Cited by-同舟云学术

Developing and validating a machine-learning algorithm to predict opioid overdose in Medicaid beneficiaries in two US states: a prognostic modelling study

Published:2022-06 Issue:6 Volume:4 Page:e455-e465
ISSN:2589-7500
Container-title:The Lancet Digital Health
language:en
Short-container-title:The Lancet Digital Health

Author:

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

Publisher

Elsevier BV

Subject

Health Information Management,Decision Sciences (miscellaneous),Health Informatics,Medicine (miscellaneous)

Reference18 articles.

1. Evaluation of machine-learning algorithms for predicting opioid overdose risk among medicare beneficiaries with opioid prescriptions;Lo-Ciganic;JAMA Netw Open,2019

2. Using machine learning to predict risk of incident opioid use disorder among fee-for-service Medicare beneficiaries: a prognostic study;Lo-Ciganic;PLoS One,2020

3. Integrating human services and criminal justice data with claims data to predict risk of opioid overdose among Medicaid beneficiaries: a machine-learning approach;Lo-Ciganic;PLoS One,2021

4. Wisdom of the CROUD: development and validation of a patient-level prediction model for opioid use disorder using population-level claims data;Reps;PLoS One,2020

5. Predicting high-risk opioid prescriptions before they are given;Hastings;Proc Natl Acad Sci USA,2020

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