Anxiety & Stress

Predicting social anxiety disorder based on communication logs and social network data from a massively multiplayer online game: Using a graph neural network.

AIM: Social anxiety disorder (SAD) is a mental disorder that requires early detection and treatment. However, some individuals with SAD avoid face-to-face evaluations, which leads to delayed detection. We aim to predict individuals with SAD based on their communication logs and social network data from a massively multiplayer online game (MMOG).

Advanced computational approaches for predicting sunflower yield: Insights from ANN, ANFIS, and GEP in normal and salinity stress environments.

Prediction of crop yield is essential for decision-makers to ensure food security and provides valuable information to farmers about factors affecting high yields. This research aimed to predict sunflower grain yield under normal and salinity stress conditions using three modeling techniques: artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and gene expression progr...

Fast, smart, and adaptive: using machine learning to optimize mental health assessment and monitor change over time.

In mental health, accurate symptom assessment and precise measurement of patient conditions are crucial for clinical decision-making and effective tre...

Rapid wall shear stress prediction for aortic aneurysms using deep learning: a fast alternative to CFD.

Aortic aneurysms pose a significant risk of rupture. Previous research has shown that areas exposed to low wall shear stress (WSS) are more prone to r...

Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer.

Heart Rate Variability (HRV) serves as a vital marker of stress levels, with lower HRV indicating higher stress. It measures the variation in the time...

Identification of 17 novel epigenetic biomarkers associated with anxiety disorders using differential methylation analysis followed by machine learning-based validation.

BACKGROUND: The changes in DNA methylation patterns may reflect both physical and mental well-being, the latter being a relatively unexplored avenue i...

Effectiveness of social robots in improving psychological well-being of hospitalised children: A systematic review and meta-analysis.

AIM: To evaluate the effectiveness of social robots in reducing pain, stress, and anxiety among hospitalised children.

Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.

BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia lev...

Efficacy and effectiveness of therapist-guided internet versus face-to-face cognitive behavioural therapy for depression via counterfactual inference using naturalistic registers and machine learning in Finland: a retrospective cohort study.

BACKGROUND: According to meta-analyses of randomised controlled trials (RCTs), therapist-guided internet-delivered cognitive behavioural therapy (iCBT...

Identifying Adolescent Depression and Anxiety Through Real-World Data and Social Determinants of Health: Machine Learning Model Development and Validation.

BACKGROUND: The prevalence of adolescent mental health conditions such as depression and anxiety has significantly increased. Despite the potential of...

Using natural language processing to identify patterns associated with depression, anxiety, and stress symptoms during the COVID-19 pandemic.

BACKGROUND: Combining data-driven natural language processing techniques with traditional methods using predefined word lists may offer greater insigh...

MechBERT: Language Models for Extracting Chemical and Property Relationships about Mechanical Stress and Strain.

Language models are transforming materials-aware natural-language processing by enabling the extraction of dynamic, context-rich information from unst...

Integrating deep learning algorithms for forecasting evapotranspiration and assessing crop water stress in agricultural water management.

The increasing impacts of climate change on global agriculture necessitate the development of advanced predictive models for efficient water managemen...

Exploring the role of oxidative stress in carotid atherosclerosis: insights from transcriptomic data and single-cell sequencing combined with machine learning.

BACKGROUND: Carotid atherosclerotic plaque is the primary cause of cardiovascular and cerebrovascular diseases. It is closely related to oxidative str...

Preliminary investigation of an artificial intelligence-based cognitive behavioral therapy training tool.

We developed an asynchronous online cognitive behavioral therapy (CBT) training tool that provides artificial intelligence- (AI-) enabled feedback to ...

The influence of generative artificial intelligence on creative cognition of design students: a chain mediation model of self-efficacy and anxiety.

INTRODUCTION: This study investigated the role of generative Artificial Intelligence (AI) in enhancing the creative cognition of design students, exam...

Development of a machine learning-based multivariable prediction model for the naturalistic course of generalized anxiety disorder.

BACKGROUND: Generalized Anxiety Disorder (GAD) is a chronic condition. Enabling the prediction of individual trajectories would facilitate tailored ma...

Deep learning based prediction of depression and anxiety in patients with type 2 diabetes mellitus using regional electronic health records.

BACKGROUND: Depression and anxiety are prevalent mental health conditions among individuals with type 2 diabetes mellitus (T2DM), who exhibit unique v...

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on indiv...

Identifying Neuro-Inflammatory Biomarkers of Generalized Anxiety Disorder from Lymphocyte Subsets Based on Machine Learning Approaches.

INTRODUCTION: Activation of the inflammatory response system is involved in the pathogenesis of generalized anxiety disorder (GAD). The purpose of thi...