Psychiatry

NeuroCypher ASD: Machine Learning with Knowledge Graph-Based Representation for ASD Screening in Toddlers.

Autism Spectrum Disorder (ASD) screening often relies on structured questionnaires. Yet these data are not always easy to interpret or use in practice. There is a need for screening frameworks that support risk estimation, case comparison, and pattern exploration in a clear and accessible way. In this work, we present NeuroCypher ASD, a framework that combines tabular machine learning with a knowl...

Using ChatGPT for thematic analysis of qualitative interviews in cultural research: a methodological investigation.

OBJECTIVE: The use of artificial intelligence (AI) tools in clinical and psychotherapy research is gaining increasing attention. This study explores the application of a large language model (LLM), ChatGPT version 4.5, as a coding assistant for qualitative data in psychotherapy research. METHODS: Twenty-four semi-structured qualitative interviews were conducted with 12 patients with bipolar disord...

How mathematics anxiety relates to mathematical ability in AI agent-supported instruction: the moderating role of executive function.

Mathematical ability is widely recognized as a core indicator of students' cognitive development and academic achievement. However, in classroom envir...

Embodied movement markers of alliance ruptures in psychotherapy: A machine learning study.

OBJECTIVE: Alliance ruptures are central to psychotherapy process and outcome, yet therapists often fail to detect them in real time, particularly wit...

Artificial intelligence and academic anxiety? a meta-analysis.

BACKGROUND: Academic anxiety negatively impacts students' performance and well-being. Although AI technologies are increasingly used in education, fin...

An integrative NLP framework identifies multilevel linguistic phenotypes of schizophrenia across tasks.

BACKGROUND: Linguistic abnormalities in schizophrenia (SCZ) span morphological, syntactic, semantic, and discourse levels. Converging cross-linguistic...

A randomised controlled trial comparing effectiveness of audio-visual aid and ai-personalised video self-modelling interventions to reduce dental fear and anxiety in paediatric patients.

PURPOSE: Paediatric dental anxiety remains a significant challenge in clinical practice, often impacting co-operation and treatment outcomes. This ran...

Exploring the Lived Experience of Acne in the United States and the United Kingdom: Social Media Analysis.

BACKGROUND: Acne is a chronic skin condition that primarily affects adolescents and young adults but can persist into adulthood. It can have repercuss...

A fully inductive inference protocol for population GNNs in single-subject brain disorder diagnosis.

Population graph-based Graph Neural Networks (GNNs) have demonstrated superior performance in brain disease diagnosis by modeling inter-subject relati...

From the Brain Cell Atlas to Precision Neurology: A review of the application of AI-driven multi-omics in brain science.

Recent advances in multi-omics technologies have catalyzed the construction of comprehensive brain cell atlases, providing essential data foundations ...

Data-Driven Profiles of Youth Executive Function and Their Longitudinal Associations With Externalizing Problems.

OBJECTIVE: Executive function (EF) deficits are observed in externalizing disorders. However, research has yet to explore the specificity of these ass...

Trust-driven healthy engagement with conversational AI for mental health support in young adults: a mixed methods study.

Young adults aged 18-35 years increasingly engage with conversational artificial intelligence (C-AI) in everyday contexts in which they may perceive e...

Construction of a small-sample brain imaging data augmentation and explainable diagnostic model for autism based on generative adversarial networks.

BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized primarily by social communication deficits and repetitive st...

Clinically accessible eye-tracking in thyroid-associated ophthalmopathy: exploratory classification modeling and gaze allocation to disease-related periocular images.

BACKGROUND: Thyroid-associated ophthalmopathy (TAO) is an autoimmune orbital disease that may cause ocular motility abnormalities, altered periocular ...

Integrating neurobiological markers to prospectively predict adolescent non-suicidal self-injury and suicide attempts: a machine learning approach.

BACKGROUND: Suicide attempts (SA) and non-suicidal self-injury (NSSI) are closely related phenomena, both common in adolescent clinical samples. This ...

Harnessing artificial intelligence for suicidality detection.

Functional Outcome Prediction in Young Adults With Mental Health Symptoms Using Machine Learning and Large Language Models: Longitudinal Observational Study.

BACKGROUND: Functional impairments associated with mental health conditions are on the rise. Predicting functional outcomes may improve the targeting ...

Development of Data-Driven Models for Just-in-Time Digital Self-Management Advice to Improve Physical Functioning in Hip and Knee Osteoarthritis: Protocol for the e-cOAch Cross-Over Study.

BACKGROUND: Clinical guidelines recommend a stepped-care strategy for patients with hip and knee osteoarthritis that begins with nonoperative approach...

Systems-level multi-omics dissection of syndromic and idiopathic autism reveals distinct regulatory architectures, candidate molecular signatures, and potential therapeutic targets.

Biological systems operate as self-organizing information networks in which genetic, epigenetic, and regulatory interactions collectively determine fu...

Protocol for assessment of pain biomarkers in orthopaedic patients undergoing total knee arthroplasty in a tertiary care hospital and neuroimmunopharmacology laboratory in South Australia: a cross-sectional matched-subject observational study.

INTRODUCTION: Knee osteoarthritis is a leading cause of pain and disability and frequently results in total knee arthroplasty (TKA). Decisions about s...