Psychiatry

Parental Perspectives on Oral Health Care for Autistic Children With Medicaid: A Qualitative Study.

Children with special health care needs and disabilities (CSHCND), particularly those with autism, experience disproportionately high rates of oral health problems, yet the underlying factors remain insufficiently explored. This qualitative study investigated the challenges and effective strategies parents use to support the oral health of autistic children enrolled in Medicaid in one large city. ...

Feature selection leads to divergent neurobiological interpretations of brain-based machine learning biomarkers.

A central objective in human neuroimaging is to understand the neurobiology underlying cognition and mental health. Machine learning models trained on neuroimaging data are increasingly used as tools for predicting behavioural phenotypes, enhancing precision medicine and improving generalizability compared with traditional MRI studies. However, the high dimensionality of brain connectivity data ma...

Predicting adult functional outcomes in childhood-onset attention-deficit/hyperactivity disorder using multimodal MRI and machine learning: A prospective follow-up study.

Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset neurodevelopmental disorder that often persists into adulthood, leading to extens...

Psychiatric Conditions in Women With Health Problems, and the Role of Artificial Intelligence (AI) in the Well-Being of Health Professionals and the Identification of Mental Disorders.

AI-Driven Speech Analysis for Mental Health Prediction in Individuals with Voice Disorders.

BACKGROUND AND OBJECTIVE: Mental health disorders are common among individuals with voice disorders, yet applications of AI-driven speech analysis in ...

Response to comments on "Predictive machine learning algorithms for depression and anxiety disorders in six cancer types: a comprehensive multi-center population-based study".

Integrated transcriptomic and clinical analysis of autism spectrum disorder reveals structured heterogeneity and links Methyl-CpG Binding Domain Protein 2 expression with symptom severity.

AIM: Autism spectrum disorder (ASD) remains underexplored in Southeast Asia, with limited characterization of its molecular underpinnings and clinical...

Comparing Images of Depression in Mass Media and AI-Generated Pictures: Mixed Methods Study.

BACKGROUND: Images play an important role in reducing stigma related to mental health, which often is distorted in the media. In recent years, generat...

User Experience and Early Clinical Outcomes of a Mental Wellness Chatbot for Depression and Anxiety: Pilot Evaluation Mixed Methods Study.

BACKGROUND: Artificial intelligence-powered conversational agents (ie, chatbots) are increasingly popular outlets for users seeking psychological supp...

Unlocking clinical narratives: how natural language processing and artificial intelligence can address data deficits and mitigate health inequities in urgent and emergency care.

The Urgent and Emergency Care system generates a wealth of clinical information, but our ability to harness this for public health planning and to add...

AI-based autism identification from hyperspectral imaging detection of oxidative stress in pediatric red blood cells.

BACKGROUND: Oxidative stress (OS) plays a key role in many pathologies, yet the non-invasive, label-free, and cost-effective detection remains a chall...

Large-scale brain network alteration among OCD patients with suicidal thoughts and behavior: A microstate analysis of the electroencephalogram.

BACKGROUND: The prevalence of suicidality in obsessive-compulsive disorder (OCD) is understudied. Moreover, identifying neurobiological markers of sui...

A data-driven analysis of artificial intelligence applications in depression research: 2020-2025.

With the rapid advancement of artificial intelligence (AI) technologies, increasing numbers of researchers have explored the integration of AI into de...

Evaluating the heterogeneous treatment effects of major depression polygenic risk scores on self-harm using causal forest.

BACKGROUND: Self-harm, defined as non-fatal self-inflicted harm regardless of suicidal intent, is a critical global health issue influenced by the int...

AI-Assisted Classical Piano Intervention for Enhancing Resilience, Mindfulness, and Emotional Processing in Young Adults With Mild-to-Moderate Anxiety or Depression.

Mental-health-oriented interventions increasingly require structured, scalable, and nonpharmacological formats that can strengthen psychological funct...

A Call for Leadership: Lessons Learnt from a Case of Artificial Intelligence (AI)-Augmented Cognitive Behavioural Therapy (CBT).

Emotion Expression in Breast Cancer Support Seeking: Empirical Study of an Online Community.

BACKGROUND: Breast cancer affects millions of women and presents not only medical challenges but also emotional, financial, and social burdens. Beyond...

Digital Monitoring of Pre-Exposure Prophylaxis Users Through Electronic Patient-Reported Outcome Measures and Electronic Patient-Reported Experience Measures: Multicenter Prospective Study on Feasibility, Safety, and Predictive Modeling of Digital Engagement.

BACKGROUND: Digital health tools integrating electronic patient-reported outcome and experience measures (ePROMs/ePREMs) enable longitudinal monitorin...

Designing Psychologically Grounded Artificial Intelligence for Supporting Bystander-Based Cyberaggression Intervention: Mixed Methods Exploratory Study.

BACKGROUND: Cyberaggression poses a growing threat to mental health, contributing to increased distress, reduced self-esteem, and other adverse psycho...

Generative AI in disability-inclusive learning: a bibliometric and systematic literature analysis.

Generative Artificial Intelligence (GenAI) has rapidly permeated education, with growing implications for disability-inclusive practice. Objective: Th...