Anxiety & Stress

Anxiety detection using neural and physiological signals and artificial intelligence: A comprehensive review.

Anxiety disorders are a significant challenge to global health, yet current diagnostic methods rely mainly on subjective and episodic assessment. The application of artificial intelligence (AI) in combination with neural and physiological signals is a promising pathway toward objective and continuous monitoring. This review provides a comprehensive evaluation of machine learning (ML) and deep lear...

Perspective: Depression in Persons with Parkinson's Disease.

Depression is a prevalent and disabling syndrome characterized by sustained sadness and/or anhedonia, as well as cognitive and physical symptoms. In Parkinson's disease (PD), depression is both common and clinically challenging due to overlapping symptoms and complex etiologic interactions. Major depressive disorder occurs in approximately 17% of PD patients, while clinically significant depressiv...

Predicting depression treatment outcomes for cognitive behavioural therapy using machine learning: A systematic review and meta-analysis.

BACKGROUND: Cognitive behavioural therapy (CBT) is an empirically-supported treatment for depression, although some patients respond well and others d...

Smartphone-based digital phenotyping for detection of high-risk depression and anxiety in Korean community settings.

BACKGROUND: Smartphones generate continuous behavioral signals such as mobility and activity patterns, offering scalable opportunities for monitoring ...

Revisiting the NETs-CYBB-p38 MAPK axis in bronchiectasis: The underlying oxidative injury mechanism.

BACKGROUND: Bronchiectasis is a chronic neutrophilic respiratory disease frequently complicated by Pseudomonas aeruginosa (P. aeruginosa) infection. N...

Preferences, tailoring, and self-tailoring in internet-delivered treatments: lessons learned.

INTRODUCTION: Internet-delivered psychological treatments have been developed and tested in many trials and are also implemented. AREAS COVERED: The a...

Dual-Signal Amplification Strategy for Synchronous Monitoring of Stress Hormones and Metabolic Indicators.

The synchronous monitoring of stress hormones and metabolic indicators is crucial for long-term health management, yet it remains a significant challe...

Examining the Use of Consumer Wearable Devices and Digital Tools for Stress Measurement in College Students: Scoping Review of Methods.

BACKGROUND: College-aged students face persistent academic and social stress that adversely affects their mental and physical health. Digital phenotyp...

Gene expression and machine learning techniques uncover corneal biomarkers associated with oxidative stress in the myopia progression.

This study aimed to identify and validate corneal biomarkers underlying myopia using human corneal tissues. Gene expression data were analyzed to inve...

Identification of biomarkers associated with endoplasmic reticulum stress-related cell death in osteoporosis based on bulk and single-cell transcriptomic analyses and experimental validation.

Osteoporosis (OP) is a metabolic bone disease characterized by low bone mineral density (BMD), and its pathogenesis involves endoplasmic reticulum (ER...

Deciphering pharmaceutical resistance in sulfur-driven autotrophic denitrification: an integrated multi-omics artificial intelligence-driven structural biology approach.

Sulfur-driven autotrophic denitrification (SdAD) is a promising low-carbon technology for nitrogen removal; however, its stability and adaptive mechan...

Leveraging artificial intelligence to personalize treatment for eating disorders: A proof-of-concept study.

Eating disorders are complex conditions with high relapse and mortality rates, and fewer than half of adults achieve clinically significant improvemen...

Artificial intelligence (AI) for virtual reality exposure therapy (VRET): A systematic review.

OBJECTIVE: This systematic review maps what is known about using artificial intelligence (AI) to tailor virtual reality exposure therapy (VRET) to bet...

Neural signatures of human psychological resilience driven by acute stress.

Neurophysiological mechanisms underlying psychological resilience-the ability to overcome adversity-have been extensively studied in animals. However,...

A hybrid AIoT model for workplace stress prediction and intervention using social media platforms.

Nowadays, stress-related issues are more challenging for employees in the workplaces. As attitudes and practices change in the workplace, employees ar...

Nonlinear dynamical analysis of chaos, fractal complexity, and entropy in EEG signals during music therapy in ICU burn patients.

Music therapy (MT) is known to influence brain dynamics; however, its effects on nonlinear electroencephalogram (EEG) characteristics in clinical sett...

Key factors associated with social anxiety symptoms among Chinese adolescents: An exploration via machine learning models.

BACKGROUND: Numerous factors from the family environment, school contexts, and individual characteristics have been shown to be associated with adoles...

The alteration of the brainstem functional connectivity in the first episode and drug-native generalized anxiety disorder and its transcriptional patterns.

BACKGROUND: Although the brainstem abnormality has been reported in anxiety disorders, there is a scarcity of research targeting the brainstem's funct...

Convolutional neural networks detected changes in facial expressions of mice that had conditioned fear stress.

Animal models are essential for studying aversive states such as fear and pain. Facial expressions may provide non-invasive readouts of aversive state...

A Dataset of University Students' Stress and Anxiety Levels based on Questionnaires and Wearable Sensors.

Mental health issues such as stress and anxiety are highly prevalent among university students, often affecting their academic performance and overall...