AIMC Journal:
Journal of addictive diseases

Showing 1 to 8 of 8 articles

Building clinical fluency in artificial intelligence: basic knowledge for addiction medicine practitioners and researchers.

Journal of addictive diseases Sep 21, 2026
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An unsupervised machine learning analysis of biopsychosocial characteristics and treatment outcome of alcohol use disorder.

Journal of addictive diseases Aug 7, 2026
Background: Alcohol Use Disorder is a heterogeneous condition where standard severity measures often fail to predict individual treatment responses. Precision medicine requires identifying distinct biopsychosocial profiles to guide targeted intervent...
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Challenges of AI-generated stigmatizing language regarding substance use disorders.

Journal of addictive diseases May 6, 2026
Stigmatizing language describing substance use behaviors in clinical documentation and in patient education materials can harm patients and their families. Recent literature has discouraged the use of stigmatizing language in treatment settings and m...
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Adherence to the 5A and 5R smoking cessation counselling models among Turkish family physicians: a multicenter cross-sectional study.

Journal of addictive diseases Apr 3, 2026
BACKGROUND: The 5A and 5R counselling models are widely recommended frameworks for smoking cessation; however, their implementation in primary care remains inconsistent. OBJECTIVE: This multicenter cross-sectional study assessed the use of these mode...
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Assessing the clinical competence of large language models for tobacco use disorder: A multi-domain expert evaluation.

Journal of addictive diseases Mar 6, 2026
BACKGROUND: Tobacco use disorder (TUD) remains the leading preventable cause of death globally, yet fewer than one-third of users receive guideline-concordant care due to workforce shortages and training gaps. Emerging artificial intelligence (AI) sy...
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Tailored psychotherapy and AI-enhanced contingency management for co-occurring disorders in cannabis use disorder: a systematic review.

Journal of addictive diseases Feb 4, 2026
BACKGROUND: Cannabis use disorder (CUD) commonly co-occurs with depression, post-traumatic stress disorder (PTSD), anxiety, and attention-deficit/hyperactivity disorder (ADHD), resulting in poorer outcomes and underscoring the need for tailored inter...
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Real-world deployment of machine learning models for opioid overdose and opioid use disorder: a systematic review of clinical and operational lessons for addiction medicine.

Journal of addictive diseases Jan 13, 2026
BACKGROUND: Machine learning (ML) is increasingly explored for opioid overdose and opioid use disorder (OUD) detection and prevention. Regional burden is uneven: the United States currently has among the highest rates of drug-overdose deaths worldwid...
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Development and validation of machine-learning algorithms predicting retention, overdoses, and all-cause mortality among US military veterans treated with buprenorphine for opioid use disorder.

Journal of addictive diseases Jun 30, 2024
BACKGROUND: Buprenorphine for opioid use disorder (B-MOUD) is essential to improving patient outcomes; however, retention is essential.
Humans Machine Learning Algorithms Female Adult Male Middle Aged United States Opioid-Related Disorders Drug Overdose Veterans Buprenorphine Narcotic Antagonists Opiate Substitution Treatment Opiate Overdose
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