AIMC Topic: Opioid-Related Disorders

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Deep Learning Solutions for Classifying Patients on Opioid Use.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Opioid analgesics, as commonly prescribed medications used for relieving pain in patients, are especially prevalent in US these years. However, an increasing amount of opioid misuse and abuse have caused lots of consequences. Researchers and clinicia...

The distribution and redistribution of fentanyl & norfentanyl in post mortem samples.

Forensic science international
This article compares 249 post mortem case reports that were positive for fentanyl/norfentanyl. All the cases were submitted to, and analyzed by, the toxicology department of the Office of the Chief Medical Examiner, Edmonton, Alberta, Canada. This s...

Exploring trends of nonmedical use of prescription drugs and polydrug abuse in the Twittersphere using unsupervised machine learning.

Addictive behaviors
INTRODUCTION: Nonmedical use of prescription medications/drugs (NMUPD) is a serious public health threat, particularly in relation to the prescription opioid analgesics abuse epidemic. While attention to this problem has been growing, there remains a...

Intranasal Abuse Potential, Pharmacokinetics, and Safety of Once-Daily, Single-Entity, Extended-Release Hydrocodone (HYD) in Recreational Opioid Users.

Pain medicine (Malden, Mass.)
OBJECTIVES: A once-daily, extended-release hydrocodone bitartrate tablet with abuse-deterrent properties (Hysingla ER® [HYD]) is available for the treatment of chronic pain in appropriate patients. This study evaluated the intranasal abuse potential ...

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects.

IEEE transactions on bio-medical engineering
UNLABELLED: This paper introduces a method utilizing spiking neural networks (SNN) for learning, classification, and comparative analysis of brain data. As a case study, the method was applied to electroencephalography (EEG) data collected during a G...

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment.

Neural networks : the official journal of the International Neural Network Society
The paper presents a methodology for the analysis of functional changes in brain activity across different conditions and different groups of subjects. This analysis is based on the recently proposed NeuCube spiking neural network (SNN) framework and...

Investigating heterogeneous effects of an expanded methadone access policy with opioid treatment program retention: a Rhode Island population-based retrospective cohort study.

American journal of epidemiology
Following federal regulatory changes during the COVID-19 pandemic, Rhode Island expanded methadone access for opioid treatment programs (OTPs) in March 2020. The policy, which permitted take-home dosing for patients, contrasted with longstanding rest...

Automating the Addiction Behaviors Checklist for Problematic Opioid Use Identification.

JAMA psychiatry
IMPORTANCE: Individuals whose chronic pain is managed with opioids are at high risk of developing an opioid use disorder. Electronic health records (EHR) allow large-scale studies to identify a continuum of problematic opioid use, including opioid us...

Predicting postoperative chronic opioid use with fair machine learning models integrating multi-modal data sources: a demonstration of ethical machine learning in healthcare.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Building upon our previous work on predicting chronic opioid use using electronic health records (EHR) and wearable data, this study leveraged the Health Equity Across the AI Lifecycle (HEAAL) framework to (a) fine tune the previously buil...