Psychiatry

Prevalence and factors associated with suicidal ideation based on the Malaysia National Health and Morbidity Survey: A machine learning analysis.

BACKGROUND: This study estimated the prevalence of past-two-week suicidal ideation and examined its demographic, clinical, and health-related correlates in a nationally representative Malaysian sample using machine learning. METHODS: The National Health and Morbidity Survey (NHMS) 2019 in Malaysia comprised a nationally representative sample of 11,674 adults aged 18 and above. Suicidal ideation wa...

Expanding the horizon of oculomics: A narrative review on the emerging roles of the anterior segment and mobile health.

Oculomics uses the eye to gain insights into systemic health. Although initially focused on retinal imaging, oculomics now studies various ocular signs beyond the retina for their associations with systemic health. The posterior segment receives significant attention because of direct visibility of the optic nerve, retinal vasculature, and neurosensory retina; however, anterior segment oculomics m...

Artificial intelligence and mental health in the workplace: positive and negative impacts.

The mental health of workers is a crucial objective of occupational health and safety programs. Mental health issues in the workforce present a signif...

Deep learning for psychiatric genomics: from tools to applications.

The genetic architecture of psychiatric disorders is highly complex, with genome-wide association studies implicating thousands of risk loci. A centra...

Indirect, Machine Learning-Based Suicide Risk Screening: Evidence from Cross-National Validation.

Dexpression recognition from EEG based on nonlinear analysis and adaptive feature fusion.

Machine learning techniques have recently shown significant promise in electroencephalograph (EEG)-based depression recognition. However, existing met...

Medical students' mental health, quality of life, motivation, and learning approaches before, during and after COVID-19: findings from a 4-wave repeated cross-sectional survey.

This study examined changes in mental health, quality of life, academic motivation, and learning approaches before, during, and after the COVID-19, pa...

Interconnected Cognitive and Neuroimmune Impairments in Schizophrenia: Modulating Effects of Antipsychotic Type, Illness Duration, and Symptom Severity.

OBJECTIVE: Cognitive impairment in schizophrenia (SCZ) is associated with neuroinflammation and neurotrophic dysregulation. The role of pro-inflammato...

Real-World Use of a Mental Health AI Companion: Multiple Methods Study.

BACKGROUND: The rapid acceleration of large language models (LLMs) creates opportunities to expand the accessibility of mental health support; however...

What stole Chinese older adults' life satisfaction? Integrating medical statistics and machine learning with a life-course perspective using CHARLS data.

BACKGROUND: As China enters a rapidly aging era, understanding the determinants of life satisfaction among older adults has become a pressing research...

Predicting the need for electroconvulsive therapy via machine learning trained on electronic health record data.

OBJECTIVES: Electroconvulsive therapy (ECT) is an effective treatment of severe manifestations of mental illness. Since delay in initiation of ECT can...

Neuroimaging-derived brain age as a new promising biomarker in mental disorders.

Mental disorders are frequently associated with accelerated brain aging, yet the diagnostic and classificatory utility of brain age remains uncertain....

Accelerated brain aging in prolonged grief disorder of later life: Influence of comorbid depression.

BACKGROUND: Prolonged Grief Disorder (PGD) in later life may involve volumetric patterns indicative of accelerated brain aging. This study examined wh...

Integrated AI-Driven Triage and Referral for Newcomer Mental Health in Ontario: Addressing Anxiety and Depression.

Systemic barriers, including language, navigation complexity, and long specialist wait-times, result in the under-utilization of mental health service...

Using AI to Train Future Clinicians in Depression Assessment: Feasibility Study.

BACKGROUND: Depression is a major global health care challenge, causing significant individual distress but also contributing to a substantial global ...

Evaluating an AI-Enabled Mobile Mental Health Monitoring Tool Among Family Caregivers of Adults Living With Cancer: Single-Arm Feasibility and Acceptability Trial Protocol.

BACKGROUND: Psychological distress, particularly symptoms of depression and anxiety (D&A), is highly prevalent among family caregivers of individuals ...

A Multimodal Dataset for Neurophysiological and AI Applications.

Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, hyperactivity, and impulsivit...

Mechanistic signatures of comorbid PTSD with cognitive impairment implicate cortisol-induced neural toxicity.

The men and women who worked in rescue and recovery operations at the 9/11 World Trade Center site are developing cognitive impairment (CI) at mid-lif...

Feasibility of machine learning classification of depression and anxiety symptoms among college students using 3D gait and sit-to-walk biomechanics.

BACKGROUND: Depression and anxiety are common and burdensome. Objective movement assessment may complement questionnaires by providing low burden scre...

Robot-assisted therapy following stroke: what effects on quality of life, cognitive and psychosocial outcomes? A systematic review.

OBJECTIVE: Robot-assisted therapy (RAT) has shown promise in post-stroke motor recovery. However, its effects on non-motor outcomes remain unclear. Th...