Addictions

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, effective, and equitable use within opioid use disorder (OUD) treatment settings. Applying our collective experiences as OUD policy and treatment experts, we discuss 8 key challenges that OUD treatment services must contend with to make the most of these r...

Hybrid Neural network and machine learning models with improved optimization method for gut microbiome effects on the sleep quality in patients with endometriosis.

BACKGROUND AND OBJECTIVE: Endometriosis is a chronic gynecological condition known to affect the quality of life of millions of women globally, often manifesting with symptoms that impact sleep quality. Emerging evidence suggests a crucial role of the gut microbiome in regulating various physiological processes, including sleep. This study investigates the relationship between gut microbiome compo...

"Amide - amine + alcohol = carboxylic acid." chemical reactions as linear algebraic analogies in graph neural networks.

In deep learning methods, especially in the context of chemistry, there is an increasing urgency to uncover the hidden learning mechanisms often dubbe...

Accelerated brain aging in alcohol users: Insights from machine learning.

Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes.

The purpose of this study is to examine and interpret machine learning models that predict dry eye (DE)-related clinical signs, subjective symptoms, a...

A machine learning approach to investigate the role of fear of pain, personal experience, and vicarious learning in dental anxiety.

BACKGROUND: Dental anxiety is a pervasive problem worldwide, leading to avoidance of dental care, resulting in oral health problems and impacting dail...

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...

Surrogate modeling of electrospun PVA/PLA nanofibers using artificial neural network for biomedical applications.

Blending poly (lactic acid) (PLA) with poly (vinyl alcohol) (PVA) improves the strength and hydrophilicity of nanofibers, making them suitable for bio...

Comparative analysis of functional network dynamics in high and low alcohol preference mice.

Individual variability preference is a typical characteristic of alcohol drinking behaviors, with a higher risk for the development of alcohol use dis...

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...

A validity and reliability study of the artificial intelligence attitude scale (AIAS-4) and its relationship with social media addiction and eating behaviors in Turkish adults.

BACKGROUND: In recent years, there has been a rapid increase in the use of the internet and social media. Billions of people worldwide use social medi...

Application of machine learning in predicting adolescent Internet behavioral addiction.

OBJECTIVE: To explore the risk factors affecting adolescents' Internet addiction behavior and build a prediction model for adolescents' Internet addic...

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...

Machine Learning of Smoking Relapse: the Role of Racial Differences and E-Cigarette Vaping Characteristics on Former Smokers.

BACKGROUND: Machine learning models can help identify multifaceted factors influencing tobacco use transitions. A random forest model is developed to ...

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...

Transformative Effects of Mindfulness Meditation Training on the Dynamic Reconfiguration of Executive and Default Mode Networks in Internet Gaming Disorder.

BACKGROUND: Internet gaming disorder (IGD) is a pervasive global mental health issue, and finding effective treatments for the disorder has been chall...

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 ...

Robot-Assisted Stereotactic Microinjection Method for Precision Cell Transplantation in Rat and Canine Models.

Cell transplantation is a promising approach for addressing neurodegenerative conditions. In this study, we developed a robot-assisted stereotactic mi...

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...

Remote sensing of alcohol consumption using machine learning speckle pattern analysis.

SIGNIFICANCE: Alcohol consumption monitoring is essential for forensic and healthcare applications. While breath and blood alcohol concentration senso...