Psychiatry

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 suppurativa are associated with a high burden of psychiatric comorbidities, including depression, anxiety, and suicidality. Despite growing awareness of the psychosocial impact of skin diseases, mental health needs remain underaddressed in dermatologic care. Digital technologies (including teledermat...

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 transdiagnostic risk state, but scalable markers of adverse outcomes remain limited. We tested whether facial dynamics extracted from baseline videos could predict transition to any psychiatric disorder in CHR individuals. METHODS: In the SSAPP cohort, CHR participants were assessed at baseline with SIPS and SCID...

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 adequate treatment remains low. Against this backdrop,...

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 confabulations; perceiving things that are not there,...

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). Although oculomotor abnormalities during static view...

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 dentistry, improving treatment processes, operationa...

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 symptoms, posing a significant diagnostic challen...

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 remains challenging due to reliance on subjective b...

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) to treat posttraumatic stress disorder (PTSD), heal...

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 widespread integration of AI chatbots into everyday...

Methodological guidance on clinical prediction models in mental health research.

Clinical prediction models play a crucial role in advancing personalized care for mental health disorders, providing essential insights for diagnosis,...

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, driving the need for new ligands with improved saf...

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. We sought to identify clinical and psychosocial p...

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 fatigue under real-world working conditions, focus...

Neuroendocrine basis of affective behavior: what we can learn from differences in sex development (DSD).

Steroid hormones influence affective behavior and its underlying neural networks. However, distinguishing between organizational and activational horm...

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 between genetic and environmental factors. Alongside...

Enhance autism spectrum disorder detection using stacking ensemble learning model with explainable AI.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that is manifested by sensory abnormalities such as hypersensitivity to sound and touc...

Artificial intelligence in traumatic stress treatment: The TRUST framework for ethical development, clinical applications, and research advancement.

Posttraumatic stress disorder (PTSD) and depression are common diagnoses following traumatic events, with several available evidence-based interventio...

Interpretable Machine Learning to Predict Anxiety or Depression in Acute Ischemic Stroke after IV Thrombolysis: A Retrospective Cohort Study.

BACKGROUND: Acute Ischemic Stroke (AIS) represents a prevalent cerebrovascular condition characterized by significant levels of disability and mortali...