Psychiatry

eMental Health Resources for Youth: Parent Perceptions of AI Matched eMental Health Resources for Their Child.

Despite high prevalence rates of pediatric mental health challenges, estimates suggest over 50% of youth with mental health conditions have never accessed services. eMental health resources have increased over the past two decades to mitigate barriers to access. Positive attitudes towards eMental health resources have been reported in adults; however, little research has focused on parent percepti...

Between empathy and algorithms: Navigating interpersonal dynamics in AI-augmented mental health care- Discursive review.

The rapid integration of artificial intelligence (AI) into mental health practice presents both unprecedented opportunities and substantial challenges for contemporary care systems. This discursive review critically examines how AI-enabled tools intersect with the interpersonal foundations of psychotherapy, with particular attention to empathy, therapeutic alliance, and relational dynamics. Drawin...

Machine learning-based diagnosis of autism spectrum disorder in children and adolescents using eye-tracking data: a systematic review and meta-analysis.

OBJECTIVE: Eye-tracking technology has been increasingly investigated as an objective approach for distinguishing individuals with Autism Spectrum Dis...

Korean longitudinal study on digitally optimized mental healthcare: a cohort profile.

The Korean Longitudinal Study on Digitally Optimized Mental Healthcare is an innovative multicenter trial-ready cohort study. It aims to develop a dig...

Identifying the optimal predictors for adolescent mental and physical health using machine learning methods.

BACKGROUND: Adolescent health is a worldwide concern. Previous research identified many factors of mental and physical health issues, which typically ...

Structural alterations related to emotion dysregulation, anxiety and self-harm in adolescents borderline personality disorder. A source-based morphometry study.

OBJECTIVE: Previous research suggests that adolescents with BPD (aBPD) exhibit distinct neuroanatomical alterations, although methodological limitatio...

Are social robots more interesting than humans? Quantitative assessment of Joint Attention in autistic and typically developing children.

INTRODUCTION: Autism Spectrum Disorder (ASD) is characterized by deficits in social interaction and communication, including joint attention (JA) impa...

Multimorbidity and memory-related disorders in older adults: A cross-national study based on three large longitudinal cohorts.

BACKGROUND: Memory-related disorders pose a growing burden on ageing populations, yet the global understanding of how multimorbidity links to such cog...

ADHD diagnosis and biomarker detection based on multimodal graph attention convolutional neural network.

Graph neural networks (GNNs) have shown potential in analyzing brain functional networks for neuropsychiatric disorder diagnosis, yet existing GNN-bas...

Causal models and network instability in neurological and psychiatric disorders: Computational and clinical perspectives.

Self-diagnosis-the capacity of a system to detect and correct its own failures-is a defining property of adaptive systems. In the brain, recursive sel...

Combining network pharmacology, machine learning, molecular docking, molecular simulation dynamics and experimental validation to explore the mechanism of Zhenwu decoction in treating major depression through TNF-α pathways.

BACKGROUND: Major depressive disorder (MDD) is a severe psychophysiological condition characterized by cognitive decline, low energy, weight loss, ins...

A new approach in autism diagnosis: Evaluating natural interaction using point of view (POV) glasses.

This study introduces an AI-assisted method based on examiner-worn Point of View (POV) glasses and computer vision analysis to provide objective behav...

An Unsupervised Learning Approach for Multimodal Low Back Pain Stratification.

STUDY DESIGN: Cross-sectional study. OBJECTIVE: This study proposes a novel stratification framework for individuals with low back pain (LBP). The met...

Deep learning based treatment remission prediction to transcranial direct current stimulation in bipolar depression using EEG power spectral density.

Bipolar disorder is characterized by marked changes in mood and activity levels and is a leading cause of disability worldwide. We sought to investiga...

Neuroinflammation and insulin resistance in major depression and bipolar disorder: Implications for clinical trials evaluating immunometabolic targeted therapies.

Bipolar disorder (BD) and major depressive disorder (MDD) are highly prevalent, disabling psychiatric illnesses marked by substantial heterogeneity an...

A five-year risk prediction model of cardiovascular disease in individuals with bipolar disorder: a nationwide register study from Sweden.

Cardiovascular disease (CVD) risk prediction models for the general population may not provide accurate predictions in individuals with bipolar disord...

Who engages? Machine learning insights into digital mindfulness-based intervention for generalized anxiety disorder.

BACKGROUND: Although mindfulness ecological momentary interventions (MEMI) appear effective in alleviating worry symptoms, treatment engagement remain...

Screening for depressive symptoms in primary and secondary school students based on speech features: A one-year longitudinal study from Jiangsu, China.

OBJECTIVE: This study aims to develop and validate an interpretable prediction model for recognizing depression risk in primary and secondary school s...

Predicting psychological risk among college students using the Freshman Entrance Psychological Survey: A machine learning model based on LASSO-logistic regression.

OBJECTIVE: With college freshmen under increasing psychological pressures, early detection of those at risk is critical. We applied machine learning t...

Predicting perceived likelihood of future suicide attempts in youth with non-suicidal self-injury: A machine learning approach using LightGBM and SHAP.

OBJECTIVES: Non-suicidal self-injury (NSSI) is a strong predictor and a gateway to suicide attempts (SA) among youth. Therefore, understanding how ind...