Anxiety & Stress

Mapping Caregiver Needs to AI Chatbot Design: Strengths and Gaps in Mental Health Support for Alzheimer's and Dementia Caregivers

Family caregivers of individuals with Alzheimer's Disease and Related Dementia (AD/ADRD) face significant emotional and logistical challenges that place them at heightened risk for stress, anxiety, and depression. Although recent advances in generative AI -- particularly large language models (LLMs) -- offer new opportunities to support mental health, little is known about how caregivers perceiv...

Unveiling the systemic impact of airborne microplastics: Integrating breathomics and machine learning with dual-tissue transcriptomics.

Airborne microplastics (MPs) pose significant respiratory and systemic health risks upon inhalation; however, current assessment methods remain inadequate. This study integrates breathomics and transcriptomics to establish a non-invasive approach for evaluating MP-induced damage to the lungs and heart. C57BL/6 mice were exposed to polystyrene MPs (0.1 μm, 2 μm, and 10 μm), and their exhaled volati...

Real-time integrated modeling of soft tissue deformation and stress based on deep learning.

. Accurately and in real-time simulating soft tissue deformation and visualizing stress distribution are crucial for advancing surgical simulators clo...

Fine-Tuning Large Audio-Language Models with LoRA for Precise Temporal Localization of Prolonged Exposure Therapy Elements

Prolonged Exposure (PE) therapy is an effective treatment for post-traumatic stress disorder (PTSD), but evaluating therapist fidelity remains labor...

MORSE-500: A Programmatically Controllable Video Benchmark to Stress-Test Multimodal Reasoning

Despite rapid advances in vision-language models (VLMs), current benchmarks for multimodal reasoning fall short in three key dimensions. First, they...

Temporal Vegetation Index-Based Unsupervised Crop Stress Detection via Eigenvector-Guided Contrastive Learning

Early detection of crop stress is vital for minimizing yield loss and enabling timely intervention in precision agriculture. Traditional approaches ...

Human Heterogeneity Invariant Stress Sensing

Stress affects physical and mental health, and wearable devices have been widely used to detect daily stress through physiological signals. However,...

The optimization of crop response to climatic stress through modulation of plant stress response mechanisms. Opportunities for biostimulants and plant hormones to meet climate challenges

Climate change is a major threat to crop potential and is characterized by both long-term shifts in temperature and precipitation patterns as well a...

Predicting Stress, Anxiety, and Depression in Adult Men Based on Nutritional and Lifestyle Variables: A Comparative Analysis of Machine Learning Methods.

Mental health disorders like depression, anxiety, and stress (DAS) are rising globally. Understanding how diet and lifestyle influence these condition...

[EVALUATION OF SCREENING FOR PTSD USING CONSORT AI RECOMMENDATIONS WITH A LARGE LANGUAGE MODEL].

Similar to major natural disasters and large-scale wars, the events of October 7th and the retaliatory Iron Swords war resulted in both direct and ind...

Correlation Information Enhanced Graph Anomaly Detection via Hypergraph Transformation.

Graph anomaly detection (GAD) has attracted increasing interest due to its critical role in diverse real-world applications. Graph neural networks (GN...

Effect of Cumulative Exposure on the Efficacy of Paroxetine: A Population Pharmacokinetic-Pharmacodynamic and Machine Learning Analyses.

Selective serotonin reuptake inhibitors (SSRIs) are widely used in depression treatment. However, the relationship between treatment efficacy and plas...

An approach to screen susceptible rats and efficacy of an antidepressive treatment after chronic stress.

Chronic stress during life has been considered a risk factor for the development of psychiatric illness in humans. Chronic unpredictable stress batter...

Artificial intelligence driven mental health diagnosis based on physiological signals.

Mental health disorders like stress, anxiety, and depression are increasing rapidly these days. Diagnosis of mental health disorders is a matter of co...

Exploring equine behavior: Wearable sensors data and explainable AI for enhanced classification.

Understanding equine behavior through advanced monitoring technologies is crucial for improving animal welfare, optimizing training strategies, and en...

Question-based computational language approach outperform ratings scale in discriminating between anxiety and depression.

Major Depression (MD) and General Anxiety Disorder (GAD) are the most common mental health disorders, which typically are assessed quantitatively by r...

Concise multi-class anxiety disorder risk assessment: A novel advanced machine learning approach.

Rapidly assessing anxiety disorder risk is crucial for effective mental health screen and intervention. However, traditional survey tools such as DASS...

Using Machine Learning to Identify Predictors of Maternal and Infant Hair Cortisol Concentration Before and During the COVID-19 Pandemic.

Hair cortisol concentration (HCC) has been theorized to reflect chronic stress, and maternal and infant HCC may be correlated due to shared genetic, p...

Towards fast and reliable estimations of 3D pressure, velocity and wall shear stress in aortic blood flow: CFD-based machine learning approach.

In this work, we developed deep neural networks for the fast and comprehensive estimation of the most salient features of aortic blood flow. These fea...

Assessing bias in AI-driven psychiatric recommendations: A comparative cross-sectional study of chatbot-classified and CANMAT 2023 guideline for adjunctive therapy in difficult-to-treat depression.

The integration of chatbots into psychiatry introduces a novel approach to support clinical decision-making, but biases in their recommendations pose ...