Addictions

Human-AI Interaction in High-Stakes Contexts: Child Welfare Professionals' Perceptions of AI Integration.

PURPOSE: Understanding professionals' early perceptions of artificial intelligence (AI) is particularly critical in high-stakes contexts, where decisions carry ethical and legal consequences. Such perceptions can help clarify acceptable-use boundaries, identify conditions for trustworthy AI integration, and inform human-centered system design. Most prior research examines attitudes after organizat...

A recyclable, mechanically robust, and anti-freezing chitosan/polyvinyl alcohol/polyaniline conductive hydrogel for multifunctional sensing application.

Conductive hydrogels have demonstrated fascinating application potential in flexible electronics. However, conductive hydrogels often exhibit poor mechanical properties, low electrical conductivity and limited recyclability, which hinders the electrochemical performance and green sustainable usability of hydrogel sensors. Therefore, it is crucial to develop hydrogel sensors with satisfactory mecha...

Human-inspired hyperparameter optimization for long-horizon forecasting of freshwater and desalination per-capita dynamics.

Growing imbalance between freshwater availability and demand, driven by population growth, infrastructure constraints, and climate variability, has in...

Prediction of Alzheimer's disease risk factors from retinal images via deep learning: Development and validation of biologically relevant morphological associations in the UK Biobank.

BackgroundThe systemic, metabolic, lifestyle factors have established associations with Alzheimer's disease (AD) through epidemiologic and AD-specific...

A Novel Machine Learning Signature Incorporating Lipid and Inflammatory Biomarkers to Predict Pulsed Radiofrequency Efficacy in Zoster-Associated Pain.

INTRODUCTION: Pulsed radiofrequency (PRF) is a pivotal neuromodulation strategy for zoster-associated pain (ZAP); however, clinical outcomes exhibit s...

Severity-dependent alterations of functional network segregation and integration in tobacco use disorder.

BACKGROUND: Previous research on brain network topology in Tobacco Use Disorder (TUD) has been inconsistent, likely due to overlooking the heterogenei...

Machine learning-based prediction of polyvinyl alcohol product viscosity and design of optimal process conditions.

We developed a soft sensor to predict polyvinyl alcohol viscosity and designed process conditions to reach the target range. Using squared and cross t...

PREPARE: Personalised Rehabilitation via Novel AI Patient Stratification Strategies. The Case for Idiopathic Scoliosis During Growth.

Drafting an Individual Rehabilitation Project requires precise goal-setting based on functional prognosis. However, patient stratification in rehabili...

A taxonomy of states' approaches to plans of safe care.

BACKGROUND: The 2016 Comprehensive Addiction and Recovery Act amended the Child Abuse Prevention and Treatment Act (CAPTA), expanding requirements for...

Machine learning versus deep learning for screening ischemic stroke among asymptomatic population.

Ischemic stroke puts great health burden in public. However, the diagnosis is based on head CT or MRI scanning. We aim to develop classifier models to...

Alcohol consumers' receptivity to artificial intelligence-generated alcohol-cancer risk messages: An experimental study.

BACKGROUND: Alcohol is a group 1 carcinogen linked to seven cancers, yet awareness of this risk remains low in the United State. Identifying effective...

Machine learning prediction of childhood nephrotic syndrome outcomes.

BACKGROUND: Children with steroid-resistant, frequently relapsing, and steroid-dependent nephrotic syndrome experience high disease and treatment-rela...

Spontaneous oxycodone withdrawal alters behavior and oligodendrocyte-related gene expression in mice.

Negative affective signs are induced during withdrawal from acute opioid injection and increase in magnitude over repeated injections. Recent evidence...

Machine learning models to predict the recurrence of common bile duct stones after ERCP.

OBJECTIVE: To construct predictive models for the recurrence of common bile duct stones (CBDS) following endoscopic retrograde cholangiopancreatograph...

TRPV1, Endocannabinoid, and Opioid Systems in Analgesia: Molecular Mechanisms and Drug Development Strategies.

Pain modulation relies on complex molecular interactions among ion channels, G protein-coupled receptors, and intracellular signaling cascades. The Tr...

A Novel Model to Predict Progression to Death After Withdrawal of Care in Potential Donation-After-Circulatory-Death Heart Donors.

BACKGROUND: Predicting successful heart donation after circulatory death (DCD) remains a challenge. We developed a model to predict progression to cir...

Multimodal assessment of minimally conscious state and cognitive motor dissociation in neurocritical care: A critical review.

Minimally conscious state (MCS) is characterized by inconsistent but clearly discernible clinical and behavioral evidence of consciousness. Cognitive ...

Advances in Ultrasound-Guided Fascial Plane Blocks for Perioperative Acute Pain Management.

INTRODUCTION: Perioperative acute pain remains a major challenge because conventional analgesic strategies are often limited by inadequate efficacy an...

Observational study of predictors and outcomes of lung cancer in never-smokers in the UK (OLIVE): study protocol.

INTRODUCTION: Lung cancer is commonly associated with smoking. However, if considered separately, lung cancer in never-smokers (LCINS) is the seventh ...

Identifying communities at elevated risk of hepatitis C infection in Los Angeles County: an ecological study using machine learning.

BACKGROUND: Identifying communities disproportionately affected by hepatitis C infection is essential for targeted prevention and resource allocation....