AIMC Topic: Opioid-Related Disorders
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Relative importance of socioecological domains to predicting opioid-involved mortality.
PloS one
Jul 29, 2025
BACKGROUND: The opioid crisis in the United States is a complex issue with interconnected factors that lead to opioid misuse and opioid-involved mortality. This study assessed the relative importance of different risk factor domains in predicting fat...
Self-Disclosure and Social Support in a Web-Based Opioid Recovery Community: Machine Learning Analysis.
JMIR formative research
Jul 17, 2025
BACKGROUND: The opioid crisis remains a critical public health challenge, with opioid use disorder (OUD) imposing significant societal and health care burdens. Web-based communities, such as the Reddit community r/OpiatesRecovery, provide an anonymou...
Mitigating Opioid Dependence in Orthopaedic Surgery: Current Strategies and Future Directions.
British journal of hospital medicine (London, England : 2005)
Jul 4, 2025
The opioid crisis presents a significant burden to patients and healthcare systems. Orthopaedic surgery involves treating patients with significant pain demands, therefore opioid stewardship in this specialty is an important area in targeting the opi...
Sentiment Analysis Using a Large Language Model-Based Approach to Detect Opioids Mixed With Other Substances Via Social Media: Method Development and Validation.
JMIR infodemiology
Jun 19, 2025
BACKGROUND: The opioid crisis poses a significant health challenge in the United States, with increasing overdoses and death rates due to opioids mixed with other illicit substances. Various strategies have been developed by federal and local governm...
Identifying emergency department patients at high risk for opioid overdose using natural language processing and machine learning.
Journal of substance use and addiction treatment
May 3, 2025
INTRODUCTION: Emergency departments (ED) are potential sites for identifying and treating individuals at high risk for opioid overdose. This study used machine learning (ML)-based models to predict opioid overdose death in the 12 months after an ED v...
Are Treatment Services Ready for the Use of Big Data Analytics and AI in Managing Opioid Use Disorder?
Journal of medical Internet research
Apr 28, 2025
In this viewpoint, we explore the use of big data analytics and artificial intelligence (AI) and discuss important challenges to their ethical, effective, and equitable use within opioid use disorder (OUD) treatment settings. Applying our collective ...
Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults.
Nature medicine
Apr 3, 2025
Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and repeated hospital admissions. Routine screening for patients at risk for an OUD to prevent complications is not standard practice in many hospitals, lead...
A longitudinal observational study with ecological momentary assessment and deep learning to predict non-prescribed opioid use, treatment retention, and medication nonadherence among persons receiving medication treatment for opioid use disorder.
Journal of substance use and addiction treatment
Mar 22, 2025
BACKGROUND: Despite effective treatments for opioid use disorder (OUD), relapse and treatment drop-out diminish their efficacy, increasing the risks of adverse outcomes, including death. Predicting important outcomes, including non-prescribed opioid ...
Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.
Journal of psychopathology and clinical science
Mar 20, 2025
Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress notes, can be mined for clinically relevant information, including the presence of substance use an...
Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.
IEEE journal of biomedical and health informatics
Feb 10, 2025
Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk individuals, determining treatment needs, monitoring prevention and intervention efforts, and recruit...
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