Psychiatry

Gaze-Tracking-Based Tests for Autism in Children: A Diagnostic Test Accuracy Systematic Review and Meta-Analysis.

Atypical gaze patterns are consistently reported in autism, reflecting differences in social attention and interest. Gaze-tracking paradigms provide an objective way to quantify these differences and may serve as early indicators of autism. This diagnostic test accuracy systematic review and meta-analysis evaluated the performance of eye-tracking-based gaze measures in children. Following Preferre...

Altered thalamic subregional connectivity with default mode and frontoparietal networks in adolescents with depression.

BACKGROUND: The thalamus plays a pivotal role in the pathophysiology of adolescent depression, with its subregions showing functional heterogeneity. Abnormalities in the default mode (DMN) and frontoparietal networks (FPN) are associated with depressive symptoms, and both networks are closely coupled with the thalamus. This study examined, at a finer granularity, functional connectivity (FC) chang...

Differential Effects of Prenatal Depression and Anxiety on Infant Sleep: Dual-Pathway Mechanisms Involving the HPA Axis and the Gut-Brain Axis.

STUDY OBJECTIVES: Prenatal psychological distress is associated with adverse offspring outcomes, including infant sleep disturbances and altered gut m...

Prompt sensitivity of large language models in orthodontic patient counseling: a scenario-based experimental study.

BACKGROUND: Large language models (LLMs) are increasingly used as accessible sources of health information, including orthodontic patient counseling. ...

Ethical cognition, AI anxiety, and attitudes toward artificial intelligence: validation of the GAAIS, AT-EAI, and AIAS in an Albanian higher-education context.

BACKGROUND: Cross-cultural psychometric evidence on instruments measuring attitudes toward artificial intelligence (AI) remains scarce in transitional...

An interpretable predictive model for depression risk in diabetic patients: A web-based application using NHANES data.

Depression is a common comorbidity in individuals with diabetes and is associated with adverse clinical outcomes. Early identification of high-risk in...

Machine learning models to predict ICU admission of patients with COPD and depression: A retrospective cohort study.

This study aimed to develop and validate a machine learning (ML)-based predictive model to identify risk factors associated with intensive care unit (...

Artificial Intelligence Applications in Cleft Lip and Palate Diagnosis, Prediction, and Treatment: A Systematic Review and Meta-Analysis.

ObjectiveCleft lip and cleft palate are common craniofacial abnormalities, causing significant functional, esthetic, and psychosocial issues if not tr...

Clinician's Corner: Chatbots for Psychotherapy.

Molecularly Engineered Wing-Shaped Azobenzene Memristors for Logic-in-Memory and Edge Visual Intelligence.

Organic molecular resistive memory offers a promising platform to overcome the von Neumann bottleneck. Here, we report four symmetric azobenzene-based...

Real-World Engagement With a Generative AI Conversational Agent for Mental Health Support: Retrospective Descriptive Study.

BACKGROUND: Generative artificial intelligence (GenAI) conversational agents are increasingly integrated within digital mental health interventions (D...

CastNet: A three-channel EEG-based deep learning model for cross-subject depression detection.

Depression is a serious mental health condition affecting millions worldwide. In recent years, deep learning models achieved remarkable performance in...

Identifying Unique Subgroups of Emotional and Behavioral Presentations in a Large Inpatient and Community Sample of Autistic Youth.

Autistic youth exhibit wide variability in emotional and behavioral challenges, yet few studies have identified meaningful subgroups based on these pr...

Hybrid deep learning for mental workload classification using EEG with enhanced preprocessing and interpretability.

Mental workload classification is critical in safety-sensitive fields such as healthcare and aviation. However, electroencephalography-based approache...

Machine learning for mental health diagnosis: power and extensions of epistemic injustice.

Following the article of Ugar and Malele, Pozzi and De Proost provide a necessary addition to the discussion around machine learning (ML) in mental he...

EEG Connectivity Signatures in Active vs. Passive Mental Fatigue Settings.

In real-world occupational settings, mental fatigue commonly emerges from the combination of sleep deprivation with prolonged cognitive and physical w...

Distinct and Shared Molecular Mechanisms Underlie Morphological-Functional Overcoupling and Undercoupling in Major Depressive Disorder.

BACKGROUND: Major depressive disorder (MDD) exhibits significant heterogeneity in alterations of brain morphology and function, however, the potential...

Novel genetic insights into causal effects of depression on non-alcoholic fatty liver diseases partially mediated by gut microbiota.

Depression and non-alcoholic fatty liver disease (NAFLD) are increasingly recognized as interconnected disorders, yet the causal mechanisms linking th...

Expression patterns of risk genes associated with three evolutionarily relevant syndromes in rhesus macaque and human brains.

Depressive disorder (DD), Alzheimer's disease (AD), and schizophrenia (SZ) are evolutionarily relevant traits that disrupt neural networks supporting ...

Efficient epileptic seizure prediction using single channel EEG signal and knowledge distillation on deep neural networks.

Epilepsy is a common neurological disease, and in some patients, abnormal changes in brain activity typically begin before the onset of a seizure. Ele...