Psychiatry

Detecting Uncoded Self-Harm in Veterans' Electronic Health Records Using Positive and Unlabeled Learning: Retrospective Cohort Study.

BACKGROUND: Underdiagnosis and undercoding are common across mental health conditions, particularly suicide and self-harm. This leaves health care datasets lacking reliable negative examples needed for predictive modeling, phenotype prevalence estimation, and identification of individuals at elevated risk. We use positive and unlabeled (PU) learning to address this challenge. OBJECTIVE: This study...

Current status and determinants of artificial intelligence-related anxiety among healthcare professionals: A cross-sectional survey study.

AIM: The rapid development of artificial intelligence (AI) has triggered various forms of anxiety among healthcare professionals. This study aimed to assess the prevalence and correlates of AI anxiety among healthcare professionals in the context of rapid AI development, thereby furnishing empirical evidence to inform the design of institutional intervention strategies. DESIGN: A cross-sectional s...

Substance-induced manic psychosis in which delusions were corroborated by a chatbot - case report.

BACKGROUND: This case describes a substance-induced manic episode with psychotic features in which interaction with an AI (artificial intelligence) ch...

Analysis of health infrastructure and suicide rates in Brazil: a nationwide ecological spatial-temporal study, 2009-2023.

BACKGROUND: Suicide remains a major global health concern and disproportionately affects low- and middle-income countries (LMICs), where socio-economi...

Clinical learning experiences and artificial intelligence-related anxiety among midwifery students: a cross-sectional study.

BACKGROUND: Artificial intelligence (AI) is rapidly transforming healthcare practice and education, requiring students to adapt to technology-supporte...

Week-ahead prediction of depressive episodes using wearable-derived circadian biomarkers: A multicenter deep learning study with risk-based operating thresholds.

Early detection of depressive episodes is important because shorter duration of untreated illness is associated with better outcomes, yet routine care...

Health behavior risk prediction in metabolic syndrome patients: development and validation of an interpretable machine learning model via multisource heterogeneous data integration.

BACKGROUND: Metabolic syndrome (MetS) represents a major public health challenge in rural populations, particularly in resource-limited regions such a...

Suicidal Ideation in Online Spaces Through the Lens of Interpersonal Theory of Suicide: Exploratory Study of Self-Disclosure, Peer Support, and AI Responses.

BACKGROUND: Suicide is a critical global public health issue, with millions experiencing suicidal ideation (SI) each year. Global estimates suggest th...

Early Deployment of an Integrated Digital Platform (shamiriOS) for Scalable Youth Mental Health Service Delivery in Kenya: Development and Usability Study.

BACKGROUND: Scaling youth mental health services in low-resource settings requires digital infrastructure that supports not just clinical delivery but...

A data-informed multidimensional composite score for stress assessment.

Occupations such as the military, emergency responders, and athletes demand acute physical, cognitive and psychosocial effort. Individuals in these ro...

Insights into middle-aged men (40-70) who died by suicide: a nationwide mixed methods study in the Netherlands.

BACKGROUND: Globally, middle-aged men dominate suicide statistics in many regions. To understand their heightened vulnerability, we examine the interp...

Mapping Practice-Based Signals of Generative AI in Psychiatric Care: Qualitative Study of Korean Psychiatrists' Experiences, Interpretations, and Implementation Priorities.

BACKGROUND: Generative artificial intelligence (GenAI) has increasingly entered psychiatric practice through patient-facing chatbots, self-help tools,...

Heritability of the Olfactory Bulb and Its Associated Brain Network.

The olfactory bulb (OB), the first central relay of the olfactory pathway, plays a critical role in odor perception and exhibits remarkable structural...

How machine learning applied on fMRI could improve the prognosis of the post-traumatic stress disorder: A systematic review.

BACKGROUND: Post-traumatic stress disorder (PTSD) is a stressor-related disorder that affects a significant proportion of the population worldwide. De...

The effect of artificial intelligence assisted evidence-based nursing on psychological distress relief and nursing satisfaction of patients with respiratory diseases.

BACKGROUND: Patients with respiratory diseases commonly experience psychological distress. Traditional evidence‑based nursing is limited in personaliz...

Artificial Intelligence Discontinuation Effects (AI-DICE): An Emerging Phenomenon in Mental Health Applications.

Artificial intelligence (AI) has emerged as a powerful tool for fostering positive behavior change and enhancing mental health support. However, the a...

Mental health in early pregnancy: Interplay of objectively measured lifestyles, gut microbiota, and metabolomics.

Prenatal anxiety symptoms (AS) and depression symptoms (DS) in early pregnancy substantially impact maternal-infant health, but their pathophysiologic...

Predicting adolescent suicidal tendency in Chinese secondary school students: a machine learning approach with XGBoost and SHAP interpretation.

BACKGROUND: Adolescent suicide is a critical public health issue globally. Early detection of suicidal tendency remains challenging due to its conceal...

Comorbidities for Predicting Progression Independent of Relapse Activity in Multiple Sclerosis Treated With B-Cell Depletion.

BACKGROUND: Progression independent of relapse activity (PIRA) has been shown to account for a majority of the disability accumulation in relapsing-re...

Artificial Intelligence Methods in Early Detection of Autism Spectrum Disorder: A DSM-5 Criterion-Based Systematic Review.

Can Artificial Intelligence (AI) revolutionize early detection of Autism Spectrum Disorder (ASD) by offering a more objective alternative to the subje...