Addictions

Using Machine Learning to Analyze the Predictors of Life Satisfaction: Focus on Lifestyle Attitudes and Psychological Factors.

OBJECTIVES: Life satisfaction is an essential indicator of quality of life, and enhancing it can contribute to individual well-being strategies. Because it is a complex concept, a comprehensive approach is needed to address it effectively. Machine learning offers a unique statistical opportunity to address this challenge effectively. In this study, we examined how lifestyle parameters, psychologic...

Machine learning-based risk warning for adolescents' prosocial behavior.

Prosocial behavior plays a positive role in promoting adolescents' mental health and behavioral performance. Guided in ecological systems theory and social cognitive theory, this study used machine learning to identify the risk factors of adolescents' prosocial behavior, and a total of six machine learning algorithms (Logistic Regression, Naive Bayes, Decision Tree, Random Forest, KNN, and LightGB...

Imaging Primary Chronic Pain Syndromes: Current Evidence, Clinical Relevance, and Advances in MRI and PET/CT.

Primary chronic pain syndromes are increasingly understood through advanced neuroimaging techniques, which reveal consistent structural, functional, a...

Machine-learning prediction of 30-day infection-related hospitalization in advanced CKD.

BACKGROUND: Patients with advanced chronic kidney disease (CKD), defined as having an estimated glomerular filtration rate (eGFR) < 45 ml/min/1.73 m²,...

3D-Printed Conductive Aerogel Humidity Sensor for Advanced Wearable Sleep and Health Monitoring.

Recent advances in personalized sleep medicine and home-based health monitoring have grown rapidly, yet progress remains limited by the lack of comfor...

Creation of an mHealth Infrastructure to Support the Development and Delivery of mHealth Interventions: Protocol for Demonstration Projects Addressing Smoking Cessation in Cancer Care.

BACKGROUND: Cancer remains a leading cause of morbidity worldwide. To reduce this burden, scalable, effective approaches are needed to address modifia...

Colorectal cancer sidedness: prognostic implications and the predictive role of artificial intelligence.

BACKGROUND: Colorectal cancer (CRC) is a biologically heterogeneous disease in which tumor sidedness has emerged as a relevant prognostic factor. Conv...

Machine learning models for predicting metabolic syndrome to support clinical decision-making in ART-treated adults living with HIV.

BACKGROUND: Metabolic syndrome (MetS) is an emerging complication among people living with HIV (PLHIV) receiving long-term antiretroviral therapy (ART...

Identification of PANoptosis-related gene SIK1 in MASLD by bioinformatics, machine learning and experimental validation.

OBJECTIVE: Metabolic dysfunction-associated steatotic liver disease (MASLD) constitutes a chronic inflammatory condition within the spectrum of metabo...

Using deep learning to identify brain networks mediating cognitive and motor impairments in alcohol use disorder.

Alcohol Use Disorder (AUD), with a lifetime prevalence of 29.1% in the U.S., is associated with functional impairment affecting visuospatial working m...

Identifying potential ligand-receptor interactions by integrating LSTM network and the attention mechanism for cell-cell communication prediction.

BACKGROUND: Cell-cell communication (CCC) mediated by ligand-receptor (L-R) interactions is fundamental to deciphering tissue development and disease ...

Unraveling Separation Mechanisms of Propanol Isomers and Water in LTA Zeolites via Deep Potential Molecular Dynamics.

High-purity isopropanol (IPA) is one of the most widely used solvents in numerous industry processes, and its energy-efficient separation from n-propa...

An experimental and computational intelligence simulation for predicting the strength accuracy of self-compacting concrete using Linz-Donawitz Slag as industrial waste derivatives.

This study investigates the mechanical performance of self-compacting concrete (SCC) incorporating Linz-Donawitz Slag (LDS) as a partial cement replac...

Cerebrospinal fluid volume outperforms traditional measures for predicting treatment failure in infant hydrocephalus.

BACKGROUND: Endoscopic third ventriculostomy with choroid plexus cauterization (ETV/CPC) offers an alternative to shunt placement for infant hydroceph...

Identifying Key Predictors of Smoking Cessation Success: Text-Based Feature Selection Using a Large Language Model.

INTRODUCTION: The most effective way to reduce mortality and morbidity among current smokers is to quit smoking. Although about half of smokers attemp...

ChatGPT-4's Consistency, Specificity, and Inclusion of Behavior Change Techniques in Delivering Smoking Cessation Advice in Traditional Chinese: A Content Analysis.

INTRODUCTION: While ChatGPT has shown promise in health domains, its application in smoking cessation, particularly in non-English contexts, remains u...

Global incidence patterns of early-onset gastrointestinal cancers and their ecological associations with behavioural risk factors.

BACKGROUND: Early-onset gastrointestinal cancers (EOGIC) are increasingly recognised as an urgent global health concern. We aimed to describe the glob...

Effect of a Personalized Mobile Health Intervention Using Artificial Intelligence (the WARIFA App) Versus a Nonpersonalized Intervention on User-Defined Objectives, Healthy Lifestyles, and Management of Type 1 Diabetes (T1D): Protocol for a Randomized Controlled Trial.

BACKGROUND: Noncommunicable diseases are the leading cause of death worldwide. Cardiovascular and respiratory diseases, cancer, and type 2 diabetes sh...

On-site food monitoring: a smartphone-readable carbon quantum dots sensor for ethanol and dimethylamine.

Carbon quantum dots were synthesized via microwave pyrolysis using o-phenylenediamine and dimethyl 2,2'-azobis(2-methylpropionate) as precursors. Thro...

Precision pharmacology of CNS GPCRs: From biased signaling to translational therapeutics.

G protein-coupled receptors (GPCRs) represent one of the most extensively targeted receptor families in central nervous system (CNS) pharmacology. Rec...