AIMC Topic: Opioid-Related Disorders
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Identification of Subphenotypes of Opioid Use Disorder Using Unsupervised Machine Learning.
Studies in health technology and informatics
May 18, 2023
This paper aimed to detect the latent clusters of patients with opioid use disorder and to identify the risk factors affecting drug misuse using unsupervised machine learning. The cluster with the highest proportion of successful treatment outcomes w...
Development and multimodal validation of a substance misuse algorithm for referral to treatment using artificial intelligence (SMART-AI): a retrospective deep learning study.
The Lancet. Digital health
Jun 1, 2022
BACKGROUND: Substance misuse is a heterogeneous and complex set of behavioural conditions that are highly prevalent in hospital settings and frequently co-occur. Few hospital-wide solutions exist to comprehensively and reliably identify these conditi...
Bias and fairness assessment of a natural language processing opioid misuse classifier: detection and mitigation of electronic health record data disadvantages across racial subgroups.
Journal of the American Medical Informatics Association : JAMIA
Oct 12, 2021
OBJECTIVES: To assess fairness and bias of a previously validated machine learning opioid misuse classifier.
Identifying risk of opioid use disorder for patients taking opioid medications with deep learning.
Journal of the American Medical Informatics Association : JAMIA
Jul 30, 2021
OBJECTIVE: The United States is experiencing an opioid epidemic. In recent years, there were more than 10 million opioid misusers aged 12 years or older annually. Identifying patients at high risk of opioid use disorder (OUD) can help to make early c...
Clinical Performance of a Gene-Based Machine Learning Classifier in Assessing Risk of Developing OUD in Subjects Taking Oral Opioids: A Prospective Observational Study.
Annals of clinical and laboratory science
Jul 1, 2021
OBJECTIVE: To reduce the incidence of Opioid Use Disorder (OUD), multiple guidelines recommend assessing the risk of OUD prior to prescribing oral opioids. Although subjective risk assessments are available to help classify subjects at risk for OUD, ...
Big data and predictive modelling for the opioid crisis: existing research and future potential.
The Lancet. Digital health
Jun 1, 2021
A need exists to accurately estimate overdose risk and improve understanding of how to deliver treatments and interventions in people with opioid use disorder in a way that reduces such risk. We consider opportunities for predictive analytics and rou...
Development of a machine learning algorithm for early detection of opioid use disorder.
Pharmacology research & perspectives
Dec 1, 2020
BACKGROUND: Opioid use disorder (OUD) affects an estimated 16 million people worldwide. The diagnosis of OUD is commonly delayed or missed altogether. We aimed to test the utility of machine learning in creating a prediction model and algorithm for e...
Can Predictive Modeling Tools Identify Patients at High Risk of Prolonged Opioid Use After ACL Reconstruction?
Clinical orthopaedics and related research
Jul 1, 2020
BACKGROUND: Machine-learning methods such as the Bayesian belief network, random forest, gradient boosting machine, and decision trees have been used to develop decision-support tools in other clinical settings. Opioid abuse is a problem among civili...
Adult
Male
Risk Assessment
Time Factors
Anterior Cruciate Ligament Reconstruction
Humans
Female
Treatment Outcome
Narcotic Antagonists
Machine Learning
Reproducibility of Results
Databases, Factual
Pain, Postoperative
Drug Administration Schedule
Military Medicine
Decision Support Techniques
Risk Factors
Arthroscopy
Opioid-Related Disorders
Retrospective Studies
Young Adult
Anterior Cruciate Ligament Injuries
Clinical Decision-Making
Enhancing Risk Assessment in Patients Receiving Chronic Opioid Analgesic Therapy Using Natural Language Processing.
Pain medicine (Malden, Mass.)
Oct 1, 2017
OBJECTIVES: Clinical guidelines for the use of opioids in chronic noncancer pain recommend assessing risk for aberrant drug-related behaviors prior to initiating opioid therapy. Despite recent dramatic increases in prescription opioid misuse and abus...
Prescription Opioid Dependence in Western New York: Using Data Analytics to Find an Answer to the Opioid Epidemic.
Studies in health technology and informatics
Jan 1, 2017
Opioid dependence and overdose is on the rise. One indicator is the increasing trends of prescription buprenorphine use among patient on chronic pain medication. In addition to the New York State Department of Health's prescription drug monitoring pr...
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