Anxiety & Stress

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 states in animals. This study investigated whether changes in facial expressions, which are potentially consistent between humans and mice, can serve as objective indicators of fear responses and distinguish fear from pain. We analyzed changes in the faci...

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 well-being. Understanding these conditions through objective, real-world data is essential for developing effective monitoring and intervention strategies. We present a multimodal dataset that captures students' daily stress and anxiety levels throu...

Artificial intelligence perceptions and career anxiety among health sciences students.

Recent rapid developments in artificial intelligence (AI) technologies are leading to significant changes in social and economic structures. These cha...

Deep learning using electroencephalogram (EEG) data for diagnosing and predicting SSRI response in major depressive disorder.

BACKGROUND: Major Depression (MDD) is a potentially life-threatening condition that ranks among the diseases with the highest global burden. Despite i...

A Deep Learning Approach for Analyzing Brainwave Signals During Audio Meditation in Expectant Mothers: Variational Mode Decomposition with a CNN-BiLSTM Model.

Meditation has increasingly been recognized as a helpful non-pharmacological intervention to treat psychological stress, anxiety, and depression durin...

Identifying postpartum depression subtypes using natural language processing and clinical notes.

BACKGROUND: Postpartum depression (PPD) remains vastly underdiagnosed, and its clinical heterogeneity is not well understood. Diagnosis codes in elect...

Interplay between high-energy quenching and state transitions in Chlamydomonas reinhardtii: a single-cell approach.

Studying cell-to-cell heterogeneity is essential to understand how unicellular organisms respond to stresses. We introduce a single-cell analysis fram...

Attitudes toward artificial intelligence among individuals with anxiety, depression, bipolar disorders, and schizophrenia.

BACKGROUND: Artificial intelligence (AI) increasingly supports medical diagnosis, interventions, and clinical decision-making. In various domains of h...

Nurses' artificial intelligence anxiety levels, their attitudes towards artificial intelligence, and their skills in acting humanistically in nursing practices.

AIM: This study aims to investigate the levels of artificial intelligence-related anxiety among nurses, their attitudes towards the use of AI in clini...

Meta-analysis, WGCNA, and machine learning converge on a four-gene biomarker panel for heat stress tolerance in Solanum lycopersicum.

Heat stress severely compromises growth, reproduction, and yield in Solanum lycopersicum, necessitating the identification of reliable molecular bioma...

Bulliform cells: anatomical, physiological, genetic, and computational perspectives on plants' drought adaptation.

This work highlights pollen thermotolerance as vital for reproductive success under heat stress, integrating molecular regulation, gene mapping, and b...

Comparison of Written and Visual Patient Education Methods Before Urodynamic Studies: A Randomized Controlled Trial.

PURPOSE: This study compared the effects of written versus visual patient education methods on patient anxiety, procedural comprehension, hemodynamic ...

Technostress in the Era of Generative Artificial Intelligence: Mental Health Implications in Medical Education.

OBJECTIVE: Generative artificial intelligence (GenAI) has rapidly expanded across education. While its educational benefits are widely recognized, con...

Soybean grain production and nutritional quality responses under elevated CO2, high temperature, and drought.

Soybean (Glycine max L. Merr.) is an important global crop that supplies protein and oil for the food and feed industries. However, its yield and nutr...

Artificial Intelligence for Predicting Treatment Response in Patients With Anxiety Disorders After Cognitive Behavioral Therapy: Systematic Review and Meta-Analysis.

BACKGROUND: Artificial intelligence (AI) models have been increasingly explored for predicting treatment response to cognitive behavioral therapy (CBT...

Application of seasonal-adjusted hybrid models for forecasting Discomfort Index in a heat-prone region of Bangladesh.

Extreme heat and humidity pose an increasing threat to human health, labor productivity, and overall well-being, particularly in heat-vulnerable and r...

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...

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 preventi...

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...