Psychiatry

A two-step temporal data augmentation and supervised learning framework for predicting autism diagnosis at 36 months in patients with tuberous sclerosis complex.

BACKGROUND: Autism spectrum disorder (ASD) affects approximately 25-50% of children with tuberous sclerosis complex (TSC). Early identification of ASD in this high-risk population is crucial for timely intervention but remains challenging due to the heterogeneous clinical presentation and complex interplay of genetic, neurological, and environmental factors. This study aimed to integrate longitudi...

The work of the consultation in general practice: a comparison of affluent and deprived areas of Scotland using a novel consultation workload index.

BACKGROUND: The workload within GP consultations, and how this varies by deprivation, is not well known. AIM: To examine how deprivation influences GP consultation workload by developing and applying a novel consultation workload index (CWI). DESIGN & SETTING: Secondary analysis of a cross-sectional postal survey of patients who had recently consulted a GP in deprived and affluent areas of Scotlan...

The utilization of Artificial Intelligence-based conversational agents on mental health care for older adults: a scoping review.

OBJECTIVES: Conversational Agents (CAs), commonly referred to as chatbots, are increasingly employed in mental health care, with applications ranging ...

Anxiety and Depression Associated With the Dependent Use of Generative AI in Medical Students: Cross-Sectional Study.

BACKGROUND: The growing integration of artificial intelligence (AI) in higher education has transformed learning processes but also raised concerns ab...

Feasibility and Acceptability of a Prevention-Focused Screener for Perinatal Depression Risk: Mixed Methods Cohort Study.

BACKGROUND: More than 20% of perinatal women experience depression, with suicide being a leading cause of maternal death in the United States. Profess...

Smartphone gaze-tracking for accessible psychiatric assessment.

Eye movements are promising biomarkers for psychiatric and neurological disorders, yet conventional recording methods rely on bulky, expensive, and la...

A qualitative interview study investigating patient, health professional, and developer perspectives on real-world implementation of patient-centered AI systems.

Artificial intelligence (AI) systems in healthcare often fail to improve patient outcomes despite high development accuracy. We conducted semi-structu...

Intelligent diagnosis of major depressive disorder with edge convolution and contrastive learning.

Based on functional connectivity (FC) matrices derived from resting-state functional magnetic resonance imaging (rs-fMRI) data, graph neural networks ...

Surgical and hormonal gender-affirming care: cross-domain determinants and artificial intelligence-enabled expansion.

Gender-affirming surgery (GAS) and gender-affirming hormone therapy (GAHT) and are evidence-based components of care that support the health and well-...

When AI Colludes: Clinical Reliability of Training and Preference Data as a Trustworthy-AI Criterion.

BACKGROUND: Research on artificial intelligence (AI) and mental health has focused largely on harms at deployment, including chatbot safety, sycophanc...

Risks and Harms of Conversational Artificial Intelligence (CAI) Chatbot Use Among US Youth.

INTRODUCTION: Conversational AI (CAI) chatbots are widely used by adolescents for instruction, entertainment, companionship, and advice, but concerns ...

Optimisation Drift and Substitution Risk in Artificial Intelligence-Supported Personalised Mental Health Nursing: A Critical Synthesis on Therapeutic Presence and Care Biography.

INTRODUCTION: Artificial intelligence-supported personalisation is accelerating in mental health services, yet it can reclassify relationship, biograp...

The Evolving Landscape of Vision Rehabilitation: Current Status and Future Directions.

Vision impairment is increasingly recognised as a complex condition shaped not only by ocular pathology but also by cognitive, psychological, social a...

Machine Learning Prediction and Reducing Overdoses With Electronic Health Record Nudges (mPROVEN) in the Primary Care Setting: Protocol for a Cluster Randomized Controlled Trial.

BACKGROUND: Opioid overdose remains a leading cause of preventable death in the United States. Existing approaches to identify individuals at elevated...

Cultural Relevance and Acceptability of Cognitive Behavioral Therapy Techniques Adapted by AI or a Human Psychologist: Experimental Study.

BACKGROUND: Evidence-based psychological interventions are usually not accessed by marginalized groups such as refugees. Culturally adapted psychologi...

Sex-specific microbial and tryptophan signatures of depression implicate archaeal methanogens and indole-3-acetic acid only in women.

Sex differences in mental health are often overlooked, yet gut microbiota-host metabolite interactions may contribute to sexual dimorphism in depressi...

Early detection of mental health on social media using a hybrid Bi-LSTM-XGBoost model: a comparative study.

The case of mental health disorders has been a main topic in the clinical and psychological field. The advancement of computing studies, especially in...

Increased Antidepressant Use after Intensive Care for Aneurysmal Subarachnoid Haemorrhage: A Machine-Learning-Enhanced Propensity-Matched Nationwide Cohort Study.

BACKGROUND: Mood disorders after aneurysmal subarachnoid haemorrhage (aSAH) are common. Meanwhile, mood disorders are also common after intensive care...

Classifying and visualizing medication use in the ABCD study.

Medication use during adolescence provides important insight into current health and treatment patterns. However, these data are often difficult to an...

Development and validation of a machine learning-based screening tool for early detection of adolescent suicide risk.

BACKGROUND: Adolescent suicide remains a significant public health concern, yet existing suicide screening instruments primarily focus on already mani...