Psychiatry

Quality and readability of AI-generated information on bipolar disorder: a cross-sectional content analysis.

BACKGROUND: Bipolar disorder is a clinically sensitive and diagnostically complex condition in which...

Network and machine learning analysis of childhood trauma, mental health, and AI-based emotional support needs in adolescents from underdeveloped regions.

BACKGROUND: The current intervention efficacy of generative conversational artificial intelligence (...

The entropic brain today.

Introduced in 2014 and revised in 2018, the entropic brain hypothesis has accrued a wealth of suppor...

Informatics-Based Psychotherapeutic and Psychiatric Interventions in Dermatology: Scoping Review of Impacts on Skin Disease Severity and Mental Health Outcomes.

BACKGROUND: Chronic dermatologic conditions such as psoriasis, atopic dermatitis, and hidradenitis s...

Predicting transition to psychiatric disorders in clinical high-risk for psychosis subjects using machine learning and facial features.

BACKGROUND: Clinical-high-risk for psychosis (CHR) status is increasingly viewed as a transdiagnosti...

The engagement-validation loop: Sycophancy, anthropomorphic projection, and clinical risk in informal AI-based mental health support.

Approximately one billion people worldwide live with a mental disorder, yet access to minimally adeq...

Corrigendum to "Machine Learning Models for detecting Suicidal ideation in Chinese in-Patients with major depressive disorder: A Single-center retrospective study" [J. Affect. Disord. 406 (2026) 121679].

Does ChatGPT need a psychiatrist? Similarities between human psychopathology and errors in large language models.

Two striking phenomena of the human mind encountered in mental healthcare are hallucinations and con...

Valence-specific oculomotor abnormalities induced by dynamic video stimuli as a robust biomarker for schizophrenia.

BACKGROUND: Deficits in visual attention and emotional processing are core to schizophrenia (SZ). Al...

Factors affecting dentists' intention to adopt artificial intelligence: an extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) model.

PURPOSE: Advancements in science and technology have integrated artificial intelligence (AI) into de...

Discriminating bipolar depression from major depressive disorder using functional and microstructural signatures of inferior fronto-occipital fasciculus: Promising results from an MRI study.

BACKGROUND: Bipolar depression (BD-d) and major depressive disorder (MDD) share overlapping clinical...

Graph Neural Networks and sequential architectures for autism detection from eye-tracking biomarkers: a multi-site study.

BACKGROUND: Autism Spectrum Disorder (ASD) affects 1 in 100 children globally, yet early detection r...

Redesigning trauma-focused interventions to address capacity challenges in mental health systems.

Despite strong evidence supporting the use of trauma-focused evidence-based psychotherapies (EBPs) t...

Loneliness and AI chatbot dependence in young adults: the mediating role of perceived social support.

BACKGROUND AND OBJECTIVES: Rapid advancements in artificial intelligence (AI) have facilitated the w...

Methodological guidance on clinical prediction models in mental health research.

Clinical prediction models play a crucial role in advancing personalized care for mental health diso...

AI-driven QSAR modelling and virtual screening in the discovery of selective dopamine D2 receptor ligands.

The dopamine D2 receptor (DRD2) is a key therapeutic target for several neuropsychiatric disorders, ...

Predictors of Detectable Viral Load among Adolescents with HIV in Low Resource Settings who are Receiving Care in Youth-Friendly Clinics.

OBJECTIVE: Adolescents with HIV (AWH) have higher rates of detectable viral loads (DVL) than adults....

Distinct mental fatigue mechanisms under prolonged work and night shifts Implications for safety management in a real-world oil drilling site.

OBJECTIVE: This study aimed to investigate how shift work and prolonged working hours affect mental ...

Dominant cross-frequency analysis-based early diagnosis of Autism Spectrum Disorder in pediatrics using FRHIS and DSTCNN.

Autism Spectrum Disorder (ASD) is a prevalent neurodevelopmental condition that affects children's c...

Machine learning-based prediction of suicide risk: A long-term OCD cohort follow-up.

BACKGROUND: Obsessive Compulsive Disorder (OCD) is associated with an increased suicide risk in comp...

Machine learning model to identify gut microbiome-derived metabolites as potential biomarkers of autism spectrum disorder: a pilot study.

Autism Spectrum Disorder (ASD) arises from complex and not yet completely understood interactions be...