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Identifying key risk factors for intentional self-harm, including suicide, among a cohort of people prescribed opioid agonist treatment: A predictive modelling study.

BACKGROUND AND AIMS: People with opioid use disorder are at increased risk of intentional self-harm and suicide. Although risk factors are well known, most tools for identifying individuals at highest risk of these behaviours have limited clinical value. We aimed to develop and internally validate models to predict intentional self-harm and suicide risk among people who have been in opioid agonist...

Artificial Intelligence (AI)-Driven Approaches to Manage Postoperative Pain, Anxiety, and Psychological Outcomes in Surgical Patients: A Systematic Review.

Postoperative pain, anxiety, and psychological distress significantly impact surgical recovery, yet conventional management strategies often lack personalization. Artificial intelligence (AI) has emerged as a transformative tool in perioperative care, offering potential solutions through predictive analytics, real-time monitoring, and tailored interventions. This systematic review synthesizes evid...

A Randomized, Blinded, Placebo-Controlled Crossover Study of the Pharmacokinetics and Pharmacodynamics of Naloxone, Naltrexone, and Nalmefene in Methadone-Sedated Working Dogs.

A randomized, blinded, placebo-controlled crossover study was performed with eight professional working dogs to evaluate the pharmacokinetics and phar...

Supervised and unsupervised learning reveal heroin-induced impairments in astrocyte structural plasticity.

Astrocytes regulate synaptic activity across large brain territories via their complex, interconnected morphology. Emerging evidence supports the invo...

Are Treatment Services Ready for the Use of Big Data Analytics and AI in Managing Opioid Use Disorder?

In this viewpoint, we explore the use of big data analytics and artificial intelligence (AI) and discuss important challenges to their ethical, effect...

Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK.

Changes in drug use in the general population during the COVID-19 pandemic and their long-term consequences are not well understood. We employed natur...

Clinical implementation of AI-based screening for risk for opioid use disorder in hospitalized adults.

Adults with opioid use disorder (OUD) are at increased risk for opioid-related complications and repeated hospital admissions. Routine screening for p...

Identifying Patient-Reported Outcome Measure Documentation in Veterans Health Administration Chiropractic Clinic Notes: Natural Language Processing Analysis.

BACKGROUND: The use of patient-reported outcome measures (PROMs) is an expected component of high-quality, measurement-based chiropractic care. The la...

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.

BACKGROUND: Despite effective treatments for opioid use disorder (OUD), relapse and treatment drop-out diminish their efficacy, increasing the risks o...

Identifying opioid relapse during COVID-19 using natural language processing of nationwide Veterans Health Administration electronic medical record data.

Novel and automated means of opioid use and relapse risk detection are needed. Unstructured electronic medical record data, including written progress...

Developing predictive models for µ opioid receptor binding using machine learning and deep learning techniques.

Opioids exert their analgesic effect by binding to the µ opioid receptor (MOR), which initiates a downstream signaling pathway, eventually inhibiting ...

Effectiveness of Generative Artificial Intelligence-Driven Responses to Patient Concerns in Long-Term Opioid Therapy: Cross-Model Assessment.

While long-term opioid therapy is a widely utilized strategy for managing chronic pain, many patients have understandable questions and concerns rega...

Integrating Artificial Intelligence Technology Into Simulation for Pre- and Postlicensure Nursing Students.

Advances in artificial intelligence (AI) technologies have not been widely integrated into simulation education. This work examines the process of des...

AI-powered topic modeling: comparing LDA and BERTopic in analyzing opioid-related cardiovascular risks in women.

Topic modeling is a crucial technique in natural language processing (NLP), enabling the extraction of latent themes from large text corpora. Traditio...

Machine Learning-Assisted Chemical Tongues Based on Dual-channel Inclusion Complexes for Rapid Identification of Nonsteroidal Anti-inflammatory Drugs in Food.

The improper application of nonsteroidal anti-inflammatory drugs (NSAIDs) presents significant health hazards via vector food contamination. A critica...

Optimized machine learning approaches to combine surface-enhanced Raman scattering and infrared data for trace detection of xylazine in illicit opioids.

Infrared absorption spectroscopy and surface-enhanced Raman spectroscopy were integrated into three data fusion strategies-hybrid (concatenated spectr...

Detecting Opioid Use Disorder in Health Claims Data With Positive Unlabeled Learning.

Accurate detection and prevalence estimation of behavioral health conditions, such as opioid use disorder (OUD), are crucial for identifying at-risk i...

Machine learning research methods to predict postoperative pain and opioid use: a narrative review.

The use of machine learning to predict postoperative pain and opioid use has likely been catalyzed by the availability of complex patient-level data, ...

A deep learning analysis for dual healthcare system users and risk of opioid use disorder.

The opioid crisis has disproportionately affected U.S. veterans, leading the Veterans Health Administration to implement opioid prescribing guidelines...

A Review of Leveraging Artificial Intelligence to Predict Persistent Postoperative Opioid Use and Opioid Use Disorder and its Ethical Considerations.

PURPOSE OF REVIEW: Artificial intelligence (AI) offers a new frontier for aiding in the management of both acute and chronic pain, which may potential...