Anxiety & Stress

An attention-based multimodal deep learning framework integrating EEG and ECG for enhanced stress detection.

Chronic stress is an important threat in Public Health, as it negatively impacts both the Body and Mind. Current methods for measuring and identifying stress rely largely on individuals providing subjective assessments or measuring isolated physiological parameters, thereby limiting the accuracy and consistency of these approaches. This study proposes a novel approach to objectively measuring an i...

Protective Effects of Riociguat Against Contrast-Induced Nephropathy: An Experimental and Machine Learning-Based Study in Rats.

Contrast-induced nephropathy (CIN) is an important cause of acute kidney injury following exposure to iodinated contrast media, and effective preventive strategies remain limited. This study investigated the renoprotective effects of riociguat, a soluble guanylate cyclase stimulator, in an experimental rat model of CIN and explored machine-learning-based prediction of renal injury using histopatho...

Decoding core molecular mechanisms of heat-stress tolerance in Brassica napus using transcriptomics and machine learning.

Integration of conventional bioinformatics approaches with advanced machine learning and explainable AI identified 45 candidate genes and 21 top featu...

Pathways from AI-assisted learning experience to psychological resilience: The role of stress perception in medical students.

This study investigated the incidence of stressors and psychological resilience among medical students within the framework of AI-assisted (artificial...

Should AI results be disclosed in mammography reports? A randomised survey study of patient responses to concordant and discordant interpretations.

OBJECTIVES: To assess how disclosing artificial intelligence (AI) results, particularly discordant findings, affects patient trust, anxiety, follow-up...

A structural equation modeling based on the conservation of resources theory: Analyzing the relations between artificial intelligence attitude, employability, and career stress in nursing students.

BACKGROUND: The rapid rise of artificial intelligence (AI) in healthcare is reshaping nursing education and practice. There is no research examining t...

Association of inflammatory biomarkers during pregnancy and the postpartum period with the risk of postpartum anxiety symptoms.

BACKGROUND: Inflammation is pivotal in psychiatric pathophysiology, yet evidence linking inflammatory biomarkers to postpartum anxiety (PPA) remains l...

Physics-aware deep learning models for predicting the heterogeneous mechanical properties of polymeric nanostructured materials.

Developing innovative materials with superior properties has been a major engineering challenge. Rationally designed polymer nanocomposites represent ...

Nanozymes: The Emerging Frontier in Catalytic Nanomaterials and Their Therapeutic Applications.

Artificial nanomaterials known as nanozymes, which possess inherent enzyme-mimetic characteristics, have transformed environmental research, biomedici...

Integrated network toxicology and computational profiling of acetyl tributyl citrate-related mechanisms in Alzheimer's disease.

BackgroundAcetyl tributyl citrate (ATBC), an eco-friendly plasticizer, exhibits poorly characterized neurotoxic effects.ObjectiveWe integrated network...

Why nonlinear models matter: unified analysis of cognitive load, stress, and exercise using wearable physiological signals.

\textbf{Objective:} Physiological measurements obtained from wearable devices reflect complex autonomic nervous system dynamics that are often ass...

Machine Learning Prediction of Vaginal Tissue Tears Using Finite Element Simulations Informed by Planar Biaxial Testing.

PURPOSE: Vaginal tissue tearing during childbirth is a prevalent injury with potential long-term consequences, yet the mechanical factors influencing ...

Spatiotemporal clustering of state-level opioid, opioid-stimulant, and opioid-benzodiazepine polysubstance deaths across the U.S.: Hierarchical agglomerative clustering analysis.

BACKGROUND: Polysubstance use continues to complicate the US overdose landscape, with over 107,000 lives lost to drug overdoses in 2022. The present s...

Using Semiautomated WhatsApp Messages for Daily Stress Measurements: Integrated Usability and Feasibility Study.

BACKGROUND: Stress is a key determinant of health outcomes and may influence work performance. Questionnaire-based assessments of stress are typically...

A SEM-ANN analysis to examine impact of AI overreliance through a social cognitive lens: the roles of dependency, FOMO, addiction, and anxiety.

The rapid integration of artificial intelligence (AI) has transformed how people learn, work, and make decisions, while raising growing concerns about...

The dual effects of individual and contextual factors on adolescent problematic internet use: Machine learning approaches and SHAP explanations.

PURPOSE: This study applied the Interaction of Person-Affect-Cognition-Execution (I-PACE) model and the Relational Development System Theory (RDS) to ...

Deep Brain Stimulation Induces Antidepressant Effects by Restoring High-Fidelity Communication in the BNST-NAc Circuit.

Deep brain stimulation (DBS) for treatment-resistant depression (TRD) is challenged by significant individual variability in efficacy and unclear neur...

Association Between Digital Biomarkers of Health and Anxiety: Systematic Review and Meta-Analysis.

BACKGROUND: Digital biomarkers are gaining interest as proxy markers for mental health, as they enable passive and continuous data collection. However...

Effectiveness of meditation in the management of epilepsy: An updated mini systematic review of recent findings.

BACKGROUND: Epilepsy is a chronic neurological disorder characterized by altered cortical excitability. The disorder is often associated with psycholo...

Integrated multi-omics analysis identifies and validates endoplasmic reticulum stress and mitophagy-related biomarkers in MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent chronic liver diseases worldwide. Growing evidence indic...