Addictions

Natural language processing tool for extracting information about opioid overdoses in the USA from case narratives in the violent death reporting system.

BACKGROUND: Improving the infrastructure for drug overdose surveillance is critical for identifying new threats and responding to emerging trends. We aimed to develop a prototype tool using the principles of natural language processing that can extract information from the death records of drug overdose victims. METHODS: Data were obtained from the Violent Death Reporting System on drug overdose d...

Perceptions, Attitudes, and Use of AI by Medical Students: Mixed Methods Study.

BACKGROUND: AI is transforming medicine by enhancing care, reducing administrative tasks, and facilitating research. AI also raises many concerns, including a lack of clinical context awareness, data dependence, and the absence of ethical judgment. As future practitioners, medical students must be prepared for these changes. Most studies assessing students' attitudes and knowledge were conducted b...

A clinically interpretable model for predicting pharyngocutaneous fistula after total laryngectomy.

BACKGROUND: Pharyngocutaneous fistula (PCF) is a frequent complication following total laryngectomy. While various risk models exist, their practical ...

Device-measured movement behaviours and cancer incidence in a population sample of UK adults: Dual 24-hour analyses of postural and intensity compositions.

BACKGROUND: Insufficient physical activity (PA) and excessive sedentary behaviour is associated with several cancers. Personalised approaches to incre...

Associations of employment status with social media addiction, anxiety, and parenting self-efficacy among mothers of infants: a cross-sectional study using machine learning.

BACKGROUND: Differences in social media addiction, anxiety, and parenting self-efficacy according to maternal employment status have important implica...

Interpretable machine-learning survival prediction of breast cancer prognosis from lifestyle factors: evidence from UK biobank.

BACKGROUND: Understanding how lifestyle habits influence breast cancer survival is crucial for improving long-term outcomes and guiding individualized...

A subtype of ultrasonic vocalizations during palatable food consumption in rats identified by machine learning-assisted classification.

Identifying behavioral and physiological responses to rewarding stimuli is essential for understanding positive emotional states in animals and for in...

Machine Learning-Guided Near-Infrared Laser Processing for Precise Geometry Control in Microneedles with Downstream microLED-Triggered Photothermal Functionality.

Transdermal drug delivery and sensing provide non-invasive routes for localized therapy and biomarker detection. Microneedles (MNs) enable pain-free a...

Artificial intelligence-assisted detection and optical differentiation of colorectal lesions in Lynch syndrome surveillance (CADLY2): a multicentre, open-label, randomised controlled superiority trial.

BACKGROUND: Artificial intelligence (AI)-based computer-aided detection (CADe) systems improve adenoma detection in average-risk colorectal cancer scr...

Personalised approach to hypertension treatment: protocol for the HYPERMARKER randomised controlled trial.

INTRODUCTION: Blood pressure treatment response is variable in individual patients, and the choice of medical therapy is often dependent on clinician ...

Predictive Models for Time to First Opioid Use Disorder or Opioid Overdose Among Older Adults.

BACKGROUND: Limited data exist on predictive models incorporating patient-reported and claims-based measures to identify older adults at risk for opio...

Machine learning prediction of physician-assigned treatment categories from pre-procedural electronic medical record data in cardiac patients: A multiclass classification study.

Cardiovascular diseases (CVDs) remain a leading source of morbidity, mortality, and healthcare burden worldwide. In patients with coronary artery dise...

Activation of sigma non-opioid intracellular receptor 1 (S1R) receptor inhibits plexin domain containing 2 (Plxdc2) driven microglial inflammation to ameliorate depressive-like behaviours in mice.

BACKGROUND AND PURPOSE: Microglia are central regulators of neuroinflammation in depression. Drivers involved remain incompletely understood. Sigma no...

AI-enabled job demands and employee well-being: Emotional exhaustion and turnover across organizational contexts.

As artificial intelligence (AI) becomes embedded in organizational work systems, employees' psychological responses increasingly shape how AI is exper...

A bio-inspired, soft-bodied jumper.

Some species of fly larvae and nematodes achieve rapid locomotion by forming loops with their bodies, latching their heads and tails, and storing elas...

User Perspectives on Conversational Agents for Preventive Alcohol Self-Help: Qualitative Exploratory Study.

BACKGROUND: Alcohol use remains a major public health concern, and although preventive alcohol self-help interventions aim to support individuals in n...

Nonverbal AI-Based Communication Robot for Staff in Disaster-Affected Care Facilities: Exploratory ABAB Intervention Study.

BACKGROUND: Medical and welfare facilities in the Noto region of Japan were severely affected by the 2024 Noto Peninsula earthquake and subsequent tor...

Artificial intelligence with mucosal exposure devices versus artificial intelligence alone in detection of colorectal adenomas: a systematic review and meta-analysis.

BACKGROUND AND AIMS: Both artificial intelligence (AI) and mucosal exposure devices (MEDs) have been shown to improve adenoma detection rate and reduc...

Development of non-destructive durian fruit maturity detection tool based on multi-variable sensor for harvest quality optimisation.

Durian maturity critically affects consumer acceptance, market value, and postharvest losses, yet its assessment remains largely subjective. This stud...

Week-Ahead Prediction of High-Risk Drinking Episodes Among Young Adults Using Wearable Biosignals and Psychological Vulnerabilities: Prospective Observational Machine Learning Study.

BACKGROUND: Although machine learning has increasingly been used to predict mental health symptoms and maladaptive behaviors, real-world prediction of...