Addictions

See more, detect more: investigating colonic inspection techniques and polyp detection using machine learning.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer mortality despite widespread colonoscopy screening. Colonoscopy effectiveness, which can reduce CRC risk by 90%, depends largely on adenoma detection rate (ADR), a metric strongly influenced by mucosal inspection quality during withdrawal. However, ADR miss rates remain as high as 26% due to incomplete inspection. Although simulation...

Predicting Outcomes of Traumatic Brain Injury Using Machine Learning Models Among Patients at Kilimanjaro Christian Medical Centre, Tanzania: A Registry-Based Cohort Study.

BACKGROUND: Traumatic brain injury (TBI) remains a major global health burden, disproportionately affecting low- and middle-income countries (LMICs) where access to neurocritical care is limited. Accurate and context-appropriate prognostic models are crucial to guide early clinical decision-making and optimize resource allocation in such settings. This study aims to develop and evaluate machine le...

What predicts postoperative opioid prescribing and consumption? A statewide analysis of surgical quality registry data.

OBJECTIVE: Tailoring postoperative opioid recommendations to patient needs requires nuanced understanding of factors contributing to post-discharge op...

Common Challenges in Predicting Opioid-related Outcomes Using Machine Learning.

Machine learning (ML) models have been commonly utilized to predict various opioid-related outcomes and risks, including post-operative opioid use, op...

Predicting and analyzing the dielectric constant of polyvinyl alcohol reinforced with different nanofillers using machine learning modeling.

Polyvinyl alcohol (PVA) is a widely used polymer in many applications. The nanoparticles' incorporation into the polyvinyl alcohol structure can signi...

Leveraging pretrained vision transformers for classifying alcohol use disorder using raw resting-state EEG.

Alcohol Use Disorder (AUD) is a prevalent neuropsychiatric condition affecting about 28 million adults in the USA, with few objective biomarkers to as...

Temporal Drivers of Opioid-Related ED Visits: An Ensemble Machine Learning Study With Consensus-Based Feature Attribution.

Identification of modifiable risk factors for prescription opioid use disorder (OUD)-related emergency department (ED) visits (ICD-10 F11.xx) is a cli...

CDMAM phantom for Image Quality Assessment and Quality Control in digital mammography: A narrative review.

PURPOSE: The CDMAM (Contrast Detail Mammography) phantom is widely used in European mammography quality control as a subjective observer-based tool fo...

Retraction notice to Integrating Generative AI Into Evidence Synthesis: Opportunities, Safeguards, and Methodological Refinements: [JVAL Volume 29, June 2026, 4609].

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/policies/article-withdrawal). This l...

Imminent opioid overdose risk prediction using classical and machine learning survival models following first recorded opioid-related diagnosis: a prospective cohort study from the All of Us research program.

Background: Identifying patients at risk of opioid overdose in healthcare settings is critical, yet evidence on predictive models and their performanc...

Three-class obstructive sleep apnea severity assessment: a parallel AHI and ODI explainable artificial intelligence framework using craniofacial-enriched clinical data.

BACKGROUND: Machine learning models for Obstructive Sleep Apnea (OSA) diagnosis have largely inherited some structural limitations: reliance on generi...

Integrating Multimodal Data and Genomics for a Comprehensive Assessment of Cardiovascular Aging and Its Impact.

BACKGROUND: Age-related structural and functional remodeling of the heart and vessels increases cardiovascular disease (CVD) risk, yet comprehensive a...

Machine Learning Model for Predicting Suicide Risks Among Patients With Posttraumatic Stress Disorder Who Received Opioids.

BACKGROUND: The cooccurrence of posttraumatic stress disorder (PTSD) and opioid use heightens suicide risk. We aimed to develop and validate a machine...

Recycled Aggregate Green Concrete with Graphene Oxide-Coated PVA Fibers: Performance Improvement and Life Cycle Evaluation.

Recycled aggregate concrete provides a sustainable route to reduce natural aggregate consumption and promote the recycling of construction and demolit...

Assessing melting points from machine learning interatomic potentials using PBE and PBEsol exchange-correlation functionals.

Accurate prediction of a material's melting temperature is critical for materials design and high-temperature applications. In this work, we investiga...

Development and external validation of a machine learning model for predicting tigecycline-associated drug-induced liver injury.

Tigecycline (TGC) is widely used to treat severe multidrug-resistant infections but can cause drug-induced liver injury. Existing prediction studies f...

Highly sensitive self-powered pressure sensor with high power output based on electrochemical reactions for rehabilitation monitoring.

Self-powered electrochemical pressure sensors have aroused considerable research interest owing to their capability of sensing both static and dynamic...

Thermodynamics and Kinetics of CO2 Sorption and Water Remediation on Waste Polyurethane Foam-Derived Hybrids.

Converting waste into dual-function materials for both atmospheric and aqueous remediation remains a formidable challenge in realizing a circular econ...

Natural Language Processing to Identify Substance Use in Electronic Health Records: A Scoping Review.

BACKGROUND: This scoping review aimed to characterize natural language processing (NLP) techniques deployed for identifying substance use in electroni...

Eco-benign synthesis of spent vegetable oil-based biodiesel using thermally modified nanocrystalline snail shell catalysts: experimental, modeling and computational studies.

The quest to mitigate the critical challenges in the global energy landscape and carbon emission crisis and promote sustainable energy practices calls...