Psychiatry

Temporal and Cell-Specific Regulation of Synaptic Homeostasis by the Chromatin Remodeler Chd1.

Disruptions in chromatin remodelers and synaptic proteins represent major genetic risk factors for autism spectrum disorder (ASD), yet how these distinct gene classes converge to impair circuit function remains unclear. CHD2, a chromatin remodeler linked to ASD, epilepsy, and intellectual disability, regulates gene expression through epigenetic mechanisms. In Drosophila, its homologue Chd1 functio...

Utilizing stimulation-evoked hemodynamic activity to predict antidepressant response to intermittent theta-burst stimulation in adults with major depression.

BACKGROUND: The instantaneous neural response to prefrontal theta burst stimulation (TBS) may serve as predictive marker for antidepressant treatment success. This study aimed to (1) assess whether baseline theta burst stimulation (TBS)-induced prefrontal hemodynamic responses can predict treatment outcome of four weeks of TBS in adults with major depressive disorder (MDD); (2) assess the test-ret...

An artificial intelligence approach to support adolescent suicide prevention initiatives in the United States.

Adolescent suicide remains a critical public health issue in the United States, with complex, interrelated risk and protective factors operating acros...

Machine learning-based methods for predicting postpartum depression: A review.

Postpartum depression (PPD) is a widespread mental illness after delivery, which has a substantial impact on the health of both mothers and infants. M...

Association of inflammatory biomarkers during pregnancy and the postpartum period with the risk of postpartum anxiety symptoms.

BACKGROUND: Inflammation is pivotal in psychiatric pathophysiology, yet evidence linking inflammatory biomarkers to postpartum anxiety (PPA) remains l...

Anticipating incomplete patient-reported outcomes in schizophrenia: a machine learning approach to predict the occurrence of missing data.

Beyond artificial intelligence psychosis: a functional typology of large language model-associated psychotic phenomena.

A man breached Windsor Castle with a crossbow after his large language model (LLM)-based companion encouraged an assassination plan. A father's questi...

Biosignatures of cognitive basic symptoms mark a distinct neurodevelopmental pathway to schizophrenia.

Efforts to predict schizophrenia risk using biological data have been hampered by the heterogeneity of current "clinical-high-risk" (CHR-P) criteria, ...

Integrated network toxicology and computational profiling of acetyl tributyl citrate-related mechanisms in Alzheimer's disease.

BackgroundAcetyl tributyl citrate (ATBC), an eco-friendly plasticizer, exhibits poorly characterized neurotoxic effects.ObjectiveWe integrated network...

Sub-band Embedding Based EEG Spatio-Temporal Activity Representation for Emotion Recognition.

EEG-based emotion recognition is a crucial task with significant implications for mental health monitoring, affective computing, and clinical decision...

Causal Discovery in Observational Medical Research: Scoping Review.

BACKGROUND: Observational data are fundamental to medical research but present formidable challenges for causal inference. Machine learning-based caus...

Breast density reporting in Aotearoa New Zealand: policy imperatives and research priorities.

Breast density influences both breast cancer risk and the sensitivity of mammographic screening. Several countries routinely notify women of their bre...

A neurofeedback-guided EEG and BCI framework for personalized attention rehabilitation in ADHD.

The integration of game-based cognitive training with electroencephalography (EEG)-based brain-computer interaction (BCI) has demonstrated potential f...

Sleep awake detection from leg-worn wearables using deep sensor fusion.

Restful sleep is essential for health, yet many children with Attention Deficit Hyperactivity Disorder (ADHD) experience disturbances such as delayed ...

AI-Powered Documentation for Mental Health Providers: Retrospective Observational Mixed Methods Study.

BACKGROUND: Mental health providers (MHPs) face a significant administrative burden from documentation, which can contribute to burnout and reduce tim...

Smartphone Addiction, Use Preferences, and Depression Among Older Adults in the Digital Context: Machine Learning Analysis of Survey Data.

BACKGROUND: The increasing use of smartphones among older adults offers new opportunities for social connection but may also pose risks associated wit...

Voices of Innovation: Reflective Report on Integrating Artificial Intelligence-Simulated Mental Health Patient Scenarios Into Undergraduate Nursing Education in the United Arab Emirates.

Limited clinical placements for mental health courses in the United Arab Emirates have made it difficult to provide consistent experiential learning f...

Enhancing Predictive Accuracy of Mood Symptoms Using Wearable Devices and Machine Learning in Bipolar Disorder.

Spatiotemporal clustering of state-level opioid, opioid-stimulant, and opioid-benzodiazepine polysubstance deaths across the U.S.: Hierarchical agglomerative clustering analysis.

BACKGROUND: Polysubstance use continues to complicate the US overdose landscape, with over 107,000 lives lost to drug overdoses in 2022. The present s...

Transient frontal spectral events from EEG predict antidepressant response to sertraline in depression.

Resting-state scalp electroencephalography (EEG) is a promising method for predicting patient outcomes of antidepressant treatments. Machine-learning-...