AIMC Topic: Opioid-Related Disorders
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Machine learning research methods to predict postoperative pain and opioid use: a narrative review.
Regional anesthesia and pain medicine
Feb 5, 2025
The use of machine learning to predict postoperative pain and opioid use has likely been catalyzed by the availability of complex patient-level data, computational and statistical advancements, the prevalence and impact of chronic postsurgical pain, ...
A deep learning analysis for dual healthcare system users and risk of opioid use disorder.
Scientific reports
Jan 29, 2025
The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Administration to implement opioid prescribing guidelines. Veterans who receive care from both VA and non-VA providers-known as dual-system users-have an inc...
A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.
Current pain and headache reports
Jan 23, 2025
PURPOSE OF REVIEW: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potentially transform opioid prescribing practices and addiction prevention strategies. In this review paper,...
Multiomic Network Analysis Identifies Dysregulated Neurobiological Pathways in Opioid Addiction.
Biological psychiatry
Nov 29, 2024
BACKGROUND: Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. However, opioid addiction treatments have limited efficacy, meaning that additional...
Developing a Wearable Sensor-Based Digital Biomarker of Opioid Dependence.
Anesthesia and analgesia
Oct 16, 2024
BACKGROUND: Repeated opioid exposure leads to a variety of physiologic adaptations that develop at different rates and may foreshadow risk of opioid-use disorder (OUD), including dependence and withdrawal. Digital pharmacovigilance strategies that us...
Spatial patterns of rural opioid-related hospital emergency department visits: A machine learning analysis.
Health & place
Oct 13, 2024
As opioid-related overdose emergency department visits continue to rise in the United States, there is a need to understand the location and magnitude of the crisis, especially in at-risk rural areas. We analyzed sets of ZIP code level electronic hea...
Factors predicting access to medications for opioid use disorder for housed and unhoused patients: A machine learning approach.
PloS one
Sep 27, 2024
BACKGROUND: Opioid use disorder (OUD) is a growing public health crisis, with opioids involved in an overwhelming majority of drug overdose deaths in the United States in recent years. While medications for opioid use disorder (MOUD) effectively redu...
The Use of Natural Language Processing Methods in Reddit to Investigate Opioid Use: Scoping Review.
JMIR infodemiology
Sep 13, 2024
BACKGROUND: The growing availability of big data spontaneously generated by social media platforms allows us to leverage natural language processing (NLP) methods as valuable tools to understand the opioid crisis.
Classifying High-Risk Patients for Persistent Opioid Use After Major Spine Surgery: A Machine-Learning Approach.
Anesthesia and analgesia
Sep 4, 2024
BACKGROUND: Persistent opioid use is a common occurrence after surgery and prolonged exposure to opioids may result in escalation and dependence. The objective of this study was to develop machine-learning-based predictive models for persistent opioi...
AI and Big Data approaches to addressing the opioid crisis: a scoping review protocol.
BMJ open
Aug 31, 2024
INTRODUCTION: This paper outlines the steps necessary to assess the latest developments in artificial intelligence (AI) as well as Big Data technologies and their relevance to the opioid crisis. Fatal opioid overdoses have risen to over 82 998 annual...
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