Anxiety & Stress

Geometry-aware PointNet for rapid prediction of cerebral aneurysm hemodynamics.

BACKGROUND AND OBJECTIVE: Cerebral aneurysms affect 2-5% of the global population and pose a significant health risk upon rupture. While computational fluid dynamics provides detailed hemodynamic information for risk assessment, its high computational demands limit routine clinical use. This study aims to develop a deep learning model to rapidly predict three-dimensional velocity fields and wall s...

Screening, validation, and transcriptional regulation analysis of oxidative stress-related biomarkers in gestational diabetes mellitus: SH3BP5, ITGAM, PRRG1, and MIS12.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common pregnancy complication linked to adverse outcomes, highlighting the need for new diagnostic markers. This study aimed to identify oxidative stress-related genes as potential biomarkers for GDM using integrated bioinformatics and experimental validation. METHODS: The GSE70493 dataset was obtained from the Gene Expression Omnibus (GEO) data...

Predicting identity dissociation using childhood maltreatment and genetic variation in the stress-response gene FKBP5: a machine learning analysis.

Identity dissociation is challenging to detect and treat, and its etiology remains incompletely understood. Childhood maltreatment and FKBP5 polymorph...

A data-centric approach to detecting and mitigating demographic bias in pediatric mental health text.

BACKGROUND: Healthcare Artificial Intelligence (AI) offers transformative potential but often inherits biases from training data, worsening disparitie...

Task complexity and AI dependency among college students: the mediating roles of cognitive load, future anxiety, and task motivation.

PURPOSE: This study aims to clarify the associations between task complexity and Artificial Intelligence (AI) dependency among university students and...

Real-World Testing of an Artificial Intelligence Conversational Agent as an Early Intervention and Support Tool in the Mental Health Referral Care Pathway: A Mixed-Methods Study.

BACKGROUND: The incidence of mental health concerns is growing, and demand for support is exceeding service capacity. Digital tools can provide additi...

An artificial intelligence prediction model for optimizing patient selection for cardiac imaging for the investigation of suspected coronary artery disease.

AIMS: Nearly, 40% of patients undergoing elective invasive coronary angiography (ICA) are diagnosed with non-obstructive coronary artery disease (CAD)...

Unlocking plant abiotic stress resilience through biostimulants and omics-driven innovations.

Frequent changes in global climate enhance environmental cues, threaten agricultural systems, which jeopardizes food security, and impair the achievem...

Enhanced PPG-based stress recognition: a transfer learning approach to internal vs. external stress.

Objective.To develop a comprehensive physiological dataset for assessing internal and external stress and to propose robust automated stress recogniti...

Speech-to-Speech Voice-Cloning Care (SVCC) for improving ICU-acquired anxiety for critically ill patients in a tertiary hospital in Beijing, China: protocol of a randomised, controlled trial.

INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infection control and other factors, limited contact be...

Interpretable ESG-sentiment hybrid deep learning for asset return forecasting with quantified interactions and latency-aware deployment.

Accurate forecasting of financial time series increasingly relies on alternative data such as environmental, social and governance (ESG) scores and ne...

HyMSS-GAD: a hybrid multi-stage framework for multi-view graph anomaly detection with structural, contextual, and geometric reasoning.

Contribution of social determinants to symptoms of generalized anxiety disorder.

Symptoms of anxiety are known to be triggered by a range of life context factors including early life trauma, poor sleep quality, infrequent exercise,...

Development of an interpretable machine learning model-based online tool for risk identification of anxiety symptoms in Chinese older adults.

BACKGROUND: As the population aging process has accelerated, anxiety symptoms (AS) among older adults have become a critical concern. In addition to d...

In situ trophic modes and metabolic traits of the dinoflagellate Karenia in response to short-term localized warming.

Algae primarily rely on photosynthesis, but many taxa can adopt mixotrophic strategies that integrate photoautotrophic and phago-heterotrophic nutriti...

Cultivating Clarity: Integrating Zen-Informed Principles Into Contemporary Radiology Practice.

Modern radiology requires sustained attention, rapid decision-making, and emotional resilience amid increasing imaging volumes, diagnostic complexity,...

Multimodal Wearable Sensor-Based Stress Detection: Machine Learning Pipeline with Systematic Feature Selection and Key Biomarker Insights.

The increasing awareness of stress-related health impacts has driven demand for accurate, non-invasive stress detection methods, particularly those le...

Sleep quality prediction in basketball athletes using a deep learning framework with an attention mechanism based on multimodal data.

It is difficult for traditional prediction methods to comprehensively evaluate the sleep quality problems of college basketball players, which is a ke...

The dark side of AI transparency: investigating AI-induced anxiety, technostress, and consumer satisfaction through a hybrid SEM-ANN approach.

As AI-driven technologies transform customer interactions, understanding their impact on consumer satisfaction is crucial. This study investigates the...

Predicting Non-Response to Multicomponent Treatment in Fibromyalgia: Development and Validation of a Machine Learning Model.

BACKGROUND: Multicomponent programs combining therapeutic exercise, cognitive-behavioral therapy, and pain neuroscience education demonstrate overall ...