Psychiatry

Using machine learning to reveal two distinct neuroanatomical subtypes of first-episode, drug-naïve major depressive disorder: Evidence from the REST-meta-MDD project.

BACKGROUND: Major depressive disorder (MDD) is a highly heterogeneous condition, complicating biomar...

Psychosis Risk and Generative Artificial Intelligence Use Frequency, Motivations, and Delusion-Like Experiences: Cross-Sectional Survey Study.

BACKGROUND: Growth of generative artificial intelligence (GenAI) has exploded in recent years. Many ...

A data-centric approach to detecting and mitigating demographic bias in pediatric mental health text.

BACKGROUND: Healthcare Artificial Intelligence (AI) offers transformative potential but often inheri...

Development and validation of an interpretable multi-task prediction model based on heart rate variability for discriminating depression, anxiety and psychiatric comorbidities: a machine learning-driven retrospective study.

Task complexity and AI dependency among college students: the mediating roles of cognitive load, future anxiety, and task motivation.

PURPOSE: This study aims to clarify the associations between task complexity and Artificial Intellig...

Exploring interactive pathways to infant disorganized attachment in a sample of mothers with postpartum depression.

Research on interactions between child and environmental factors in the development of infant disorg...

Bridging Science and Subjectivity: Evolving Evidence, Emerging Technologies and the Call for Personalised Psychotherapy: Créer une passerelle entre la science et la subjectivité : Évolution des données probantes, arrivée de nouvelles technologies et appel à une psychothérapie personnalisée.

Psychotherapy Research in the Era of Digital Health and AIThe integration of digital health technolo...

Real-World Testing of an Artificial Intelligence Conversational Agent as an Early Intervention and Support Tool in the Mental Health Referral Care Pathway: A Mixed-Methods Study.

BACKGROUND: The incidence of mental health concerns is growing, and demand for support is exceeding ...

ADBrainNet: a deep neural network for Autism Spectrum Disorder (ASD) and Attention Deficit and Hyperactivity Disorder (ADHD) classification using resting-state fMRI images based on explainable artificial intelligence.

Autism Spectrum Disorder (ASD) and Attention Deficit and Hyperactivity Disorder (ADHD) are two psych...

Comparing Risk Prediction for Suicide Attempts and Deaths After Emergency Department Visits for Individuals With Mental Health Disorders.

Objective: To identify and compare predictors of nonfatal and fatal suicidal events within 180 days ...

A systematic review of artificial intelligence in child and adolescent interventions: from psychotherapy to developmental support.

Speech-to-Speech Voice-Cloning Care (SVCC) for improving ICU-acquired anxiety for critically ill patients in a tertiary hospital in Beijing, China: protocol of a randomised, controlled trial.

INTRODUCTION: Intensive care unit (ICU) visiting restrictions in hospitals, implemented due to infec...

Identification of metabolism and inflammation-related biomarkers and potential drugs for schizophrenia based on comprehensive bioinformatics and machine learning.

Functional connectivity-based classification and subtyping of major depression for precision mental health: An ensemble graph neural network approach.

Major depressive disorder (MDD) remains clinically diagnosed based on subjective symptoms rather tha...

Contribution of social determinants to symptoms of generalized anxiety disorder.

Symptoms of anxiety are known to be triggered by a range of life context factors including early lif...

Development of an interpretable machine learning model-based online tool for risk identification of anxiety symptoms in Chinese older adults.

BACKGROUND: As the population aging process has accelerated, anxiety symptoms (AS) among older adult...

Shift to the core: Abnormal core-periphery global topography in unipolar and bipolar depression.

This study explores the global signal topography of core and periphery brain networks in Major Depre...

From linguistic analyses to large language models: A scoping review of methods used to investigate language features in depression research.

Clinicians have long relied on communication to identify mental states, as many mental health condit...

The cerebro-cerebellar system: Integrative roles in motor control, cognition, and neuropsychiatric disorders.

The cerebro-cerebellar system, a network of bidirectional loops between the cerebellum and cerebral ...

From stigma to sanctuary: A conceptual framework for M-PODS, a low-cost, AI-powered mental health pod.

A conceptual framework for an AI driven mental health pod (M-PODS), that can help to step care and t...

Multimodal Wearable Sensor-Based Stress Detection: Machine Learning Pipeline with Systematic Feature Selection and Key Biomarker Insights.

The increasing awareness of stress-related health impacts has driven demand for accurate, non-invasi...