Psychiatry

Anxiety & Stress

Latest AI and machine learning research in anxiety & stress for healthcare professionals.

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Showing 1461-1480 of 4,207 articles

The effect of psychotherapy on the multivariate association between insomnia and depressive symptoms in late-life depression

Late-life depression (LLD) is prevalent in older adults and linked to increased disability, mortality, and suicide risk. Insomnia symptoms are considered common remaining symptoms of LLD following treatment. However, the multivariate relationship between insomnia and depressive symptoms and the impact of psychotherapy on their interrelationship is insufficiently assessed. We used data from 185 pat...

Predicting Positive Psychological States using Machine Learning and Digital Biomarkers from Everyday Wearable Data

Wearable devices offer continuous physiological data collection, presenting new opportunities for real-world mental health monitoring. Previous research has primarily emphasized detecting stress and psychological states associated with mental illnesses, whereas predicting positive psychological states, such as self-esteem, positive affect, and meaning in life, remains underexplored. In this study,...

The allostatic overload in pregnancy during the COVID-19 pandemic and potential effects on the health of the mother-child dyad: Study Protocol

Allostatic load refers to the cumulative burden of stress and life events that involve the interaction of various physiological systems at differing l...

Key predictors of maternal mild depression and anxiety in low resource settings: A machine learning approach

Maternal mental health (MMH) disorders, particularly depression and anxiety, are major public health concerns in low- and middle-income countries (LMI...

Biomarkers of the Microbiome-Skin-Brain Axis in Stress and Depression: Fingerprinting of Highly Volatile Compounds in Axillary Sweat via Gas Chromatography-Ion Mobility Spectrometry

Difficulty in the diagnosis of high stress and depression has been recognized conventionally depending on the observation of patient symptoms and psyc...

Machine Learning-Enabled EEG Biomarkers Predict Divergent Antidepressant and Placebo Response in a Clinical Trial of Major Depression

Major depressive disorder (MDD) is a heterogeneous neuropsychiatric disorder with highly variable antidepressant outcomes. In randomized controlled tr...

Comparing Machine and Deep Learning Models for Pediatric Anxiety Classification using Structured EHRs and Area-based Measures of Health Data

This study investigates the performance of various machine learning (ML) and deep learning (DL) models to classify pediatric patients at risk of anxie...

COVID-19 modulates pregnancy outcomes

The COVID-19 pandemic exposed many pregnant individuals to SARS-CoV-2. Literature suggests a link between gestational COVID-19 and adverse gestational...

Mindfulness-Based Interventions using Artificial Intelligence: A Systematic Review Protocol

Mindfulness-based interventions (MBIs) have gained significant recognition as effective approaches for promoting mental health and well-being. With ra...

AI-Derived Splenic Response in Cardiac PET Predicts Mortality: A Multi-Site Study

Inadequate pharmacologic stress may limit the diagnostic and prognostic accuracy of myocardial perfusion imaging (MPI). The splenic ratio (SR), a meas...

Prediction of impulse control disorders in Parkinson’s disease: a longitudinal machine learning study

Impulse control disorders (ICD) in Parkinson’s disease (PD) patients mainly occur as adverse effects of dopamine replacement therapy. Despite several ...

Conversational AI in Therapy: Current Applications and Future Directions in Mental Health Support

This paper delivers a rigorous mixed-methods synthesis of conversational AI applications in mental health therapy, analyzing 47 randomized controlled ...

War, Diets, and Mental Health: PTSD in Ukrainian Youth

The ongoing war in Ukraine has exposed young adults to sustained psychological stress, elevating their risk of developing post-traumatic stress disord...

Incremental diagnostic value of AI-derived coronary artery calcium in 18F-flurpiridaz PET Myocardial Perfusion Imaging

Positron Emission Tomography (PET) myocardial perfusion imaging (MPI) is a powerful tool for predicting coronary artery disease (CAD). Coronary artery...

clickBrick Prompt Engineering: Optimizing Large Language Model Performance in Clinical Psychiatry

Prompt engineering has the potential to enhance large language models’ (LLM) ability to solve tasks through improved in-context learning. In clinical ...

Multicenter Evaluation of Interpretable AI for Coronary Artery Disease Diagnosis from PET Biomarkers

Positron emission tomography (PET)/CT for myocardial perfusion imaging (MPI) provides multiple imaging biomarkers, often evaluated separately. We deve...

Patterns of Suicidal Stress Disclosure on Social Media: Integrating Computational and Qualitative Approaches

The lack of understanding of how individuals communicate suicidal stress hinders global suicide intervention plans and practices. This study identifie...

Machine learning based phenotyping of the response to mindfulness for chronic low back pain

Millions of people each year suffer from chronic low back pain (cLBP), which adversely affects their physical and mental health. While non-pharmacolog...

Developing an AI-Enhanced Individualized Prediction Tool for Psychopathological Symptoms in Vietnam: A Study Protocol

Artificial intelligence (AI) is increasingly leveraged in mental healthcare for early detection, monitoring, and personalized intervention. However, m...

Neuroimaging Correlates of Post-Stroke Pain After Ischemic Stroke: Secondary Analysis of the INSPiRE-TMS Trial

Post-stroke pain (PSP) affects nearly half of stroke survivors, severely compromising quality of life. The causes of PSP remain underexplored, althoug...

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