Psychiatry

Causal Discovery in Observational Medical Research: Scoping Review.

BACKGROUND: Observational data are fundamental to medical research but present formidable challenges...

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. Sev...

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-compu...

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

Restful sleep is essential for health, yet many children with Attention Deficit Hyperactivity Disord...

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

BACKGROUND: Mental health providers (MHPs) face a significant administrative burden from documentati...

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...

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 diffi...

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 l...

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 outcom...

Multimodal machine learning for major depressive disorder: Integrating EEG functional connectivity and clinical variables to enhance diagnostic accuracy.

The diagnosis of Major Depressive Disorder (MDD) relies heavily on subjective clinical assessments. ...

Stack-Engineered Mode Selection in PtMn/(Co/Pd)n Multilayers Enables Deterministic Analog Spin-Orbit Torque Synapses.

Spin-orbit-torque (SOT) devices that support both binary and analog switching can bridge spintronic ...

Mortality score in chronic coronary syndrome: prediction model from the ISCHEMIA trial.

AIMS: Accurate stratification of mortality risk is essential for management of chronic coronary synd...

Construction and validation of a predictive model for suicidal attempts in patients with mood disorders after discharge based on machine learning methods: A two-year follow-up study.

BACKGROUND: Suicide attempts (SA) in patients with mood disorders (MD) should be paid enough attenti...

Classification of functional near-infrared spectroscopy (fNIRS) signals in schizophrenia and bipolar disorder using deep learning methods.

BACKGROUND: Schizophrenia (SCZ) and Bipolar Disorder (BD) are prevalent mental disorders. This study...

A SEM-ANN analysis to examine impact of AI overreliance through a social cognitive lens: the roles of dependency, FOMO, addiction, and anxiety.

The rapid integration of artificial intelligence (AI) has transformed how people learn, work, and ma...

Machine learning-based prediction model for fall risk among individuals with arthritis in China: an analysis using the China Health and Retirement Longitudinal Study (CHARLS) database.

BACKGROUND: Falling has become a global public health problem. Individuals with arthritis have a hig...

The Performance of Wearable Device-Based Artificial Intelligence in Detecting Depression: Systematic Review and Meta-Analysis.

BACKGROUND: In recent years, advances in wearable sensor technology and artificial intelligence (AI)...

EEG based detection of schizophrenia using asymmetry of entropy and CNN-LSTM model.

Schizophrenia is a severe neuropsychiatric disorder with a significant impact on individual's real-l...

Functional brain network modulation following conventional and optimized HD-tDCS in major depressive disorder: A machine learning prediction of treatment response.

BACKGROUND: Major depressive disorder (MDD) is a prevalent and disabling condition that remains inad...

DisNet : Learning interpretable depression representations in speech.

Speech-based depression detection (SDD) offers an objective and convenient method for depression scr...