Anxiety & Stress

A Foundation Model for Wearable Movement Data in Mental Health Research.

Wearable movement data is collected by nearly all commercially available smartwatches and is a valuable resource for mental health research, reflecting fine-grained temporal behavioral trends. Despite its promise, the development of foundation models for health wearable modeling remains limited when compared to clinical image and text analysis. We designed transformers with patch embeddings and us...

Application of artificial intelligence-assisted education for postoperative pulmonary rehabilitation: a hybrid model of AI and nurse-driven support.

OBJECTIVE: To explore the clinical value of AI-assisted pulmonary rehabilitation education in patients undergoing thoracoscopic surgery for lung cancer. METHODS: This was a non-randomized, two-period comparative study comparing AI-assisted education with routine education for postoperative pulmonary rehabilitation in lung cancer patients. Patients who underwent thoracoscopic radical lung cancer su...

Multimodal Personalized Mobile Health Just-in-Time Adaptive Intervention for Occupational Stress Management: Pilot Study.

BACKGROUND: As digital health solutions gain traction, there is an urgent need for effective, person-centered stress management tools for employees. A...

Exhaled Breath Performance in Diagnosing Ischemic Heart Disease Utilizing a Machine Learning Model.

Ischemic heart disease (IHD) remains the leading global cause of mortality and morbidity. Current diagnostic approaches face significant limitations i...

The association between artificial intelligence anxiety and occupational anxiety among emergency department healthcare workers.

INTRODUCTION: While the integration of artificial intelligence (AI) into healthcare services has the potential to improve the quality of patient care ...

Understanding student mental health: An explainable pattern analysis approach.

Student mental health is a growing global concern, with stress, nervousness, and related psychological challenges negatively affecting academic perfor...

Current themes of AI in mental health: Actionable evidence and guardrails for mood and anxiety care.

Currently, artificial intelligence (AI) is clinically relevant to mood and anxiety care, but the evidence base is uneven across use cases. This narrat...

Heterogeneous pathways to depressive and anxiety disorders: A cluster-based predictive study in a nationwide longitudinal cohort.

BACKGROUND: Early prediction of depressive and anxiety disorders is challenging due to substantial heterogeneity in risk pathways. Conventional machin...

Composite Heat Wave Risk (CHWR) framework using Principal Component Analysis (PCA) and machine learning for assessing agro community resilience.

Scientific literature highlights that rising mean temperatures, combined with increasing frequency and duration of extreme heat events, pose risks to ...

Toward precision prevention: machine learning-identified risk and protective factors for distinct bullying victimization types among Chinese adolescents.

BACKGROUND: Bullying victimization among Chinese adolescents manifests in distinct types (verbal, physical, relational, cyberbullying) with unique adv...

Wireless, skin-interfaced multimodal sensing system for continuous psychophysiological monitoring-A wearable polygraph device.

Accurate, continuous monitoring of psychophysiological states is central to understanding stress and autonomic dysfunction across diverse medical cont...

Adrenal gland dysfunction in males with cluster headache.

BACKGROUND: Cluster headache is associated with compensated hypogonadism in males, suggesting impaired testicular steroidogenesis. It is unknown if ad...

CFTR modulator therapy reshapes airway inflammation in cystic fibrosis: Insights from proteomics and machine learning.

BACKGROUND: CFTR modulators, including Elexacaftor/Tezacaftor/Ivacaftor (ETI), have markedly improved clinical outcomes for people with cystic fibrosi...

Hierarchical Structural-Interfacial Engineering with Dynamic Soft-Hard Cross-Linking Enables Full-Range, Ultrasensitive MXene Piezoresistive Sensors.

Human tactile perception inspires flexible piezoresistive sensors, yet simultaneously achieving high sensitivity, a wide pressure range, and mechanica...

Integrative Bioinformatics, Experimental Validation, and Interpretable Machine Learning Reveal Oxyresveratrol-Mediated Protection Against Cadmium-Induced Lung Adenocarcinoma-Related Transcriptional Dysregulation.

Cadmium (Cd) is a toxic heavy metal strongly implicated in lung adenocarcinoma (LUAD) through mechanisms involving oxidative stress, epigenetic dysreg...

Digital patient education and its role in overcoming dental anxiety and barriers to endodontic care.

Dental fear and anxiety (DFA) serve as a significant obstacle to oral healthcare, affecting approximately 15% of the adult population. In endodontics,...

ASA-ED: Automated Stress Assessment Via Emotion-Awareness-Driven Deep Hybrid Learning Fusing MTF and RP.

Currently, most studies on mental stress evaluation mainly focus on classification tasks, while research on accurately estimating continuous stress le...

Comparing machine and deep learning models for pediatric anxiety classification using structured EHRs and area-based measures of health data.

OBJECTIVE: This retrospective, case-control study with internal validation evaluates the performance of machine learning (ML) and deep learning (DL) m...

Harnessing meta-analysis and artificial intelligence to reveal conserved regulatory biosignatures of abiotic stress in soybean.

BACKGROUND: Soybeans are widely cultivated worldwide as an important source of edible vegetable oil and protein. Due to climate change, it is repeated...

Identification of ribosomal stress related signature genes and immune microenvironment analysis in ovarian cancer based on multi-machine learning.

BACKGROUND: Ovarian cancer (OC) is a highly aggressive malignancy with poor prognosis and limited response to immunotherapy. Ribosomal stress, a cellu...