Psychiatry

Modeling Diabetes Risk and Progression With Public Health Data: Ontology-Guided, Simulation-Capable Digital Twin Study.

BACKGROUND: Digital twins (DTs) offer a paradigm for health care by enabling data-driven, simulation-capable representations of individual health trajectories. However, DT development remains limited by the scarcity of standardized, temporally structured, and multidomain data suitable for modeling chronic disease progression. Most existing DT studies rely on narrowly scoped or proprietary datasets...

Use of AI to Predict and Support Medication Adherence in Patients With Breast Cancer: Systematic Review.

BACKGROUND: Oral medications are commonly used in the treatment of breast cancer (BC), despite high rates of nonadherence. As adherence is fundamental for optimal treatment, finding ways to effectively improve it is important. Artificial intelligence (AI) is being widely applied to health care. OBJECTIVE: This review aims to offer an overview of the contribution of AI to medication nonadherence am...

Predicting Somatization Risk Among Infectious Disease Disaster Frontline Nurses Using Machine Learning.

This study aimed to identify key risk factors associated with high-somatization risk among frontline nurses responding to infectious diseases, utilizi...

Impaired regional structure-function coupling as novel neurophenotype: mechanistic insights and diagnostic exploration in treatment-resistant depression.

Treatment‑resistant depression (TRD) is one of the toughest clinical challenges in psychiatry, characterized by high recurrence, heavy disease burden,...

Predicting student mental health through entropy-based features and interpretable cross-attention transformer networks.

Mental health is becoming a major concern for students in today's fast-changing world. Mental health challenges have impact on every aspect of life in...

The effect of robot-based interventions on depression in older adults with cognitive impairment: A systematic review and meta-analysis.

OBJECTIVE: To assess the effectiveness of robot-based interventions in improving depressive symptoms among older adults with cognitive impairment, and...

Rhythms of mood: Bidirectional regulation of molecular clocks and neurotransmission in affective disorders.

Mood disorders, primarily major depressive and bipolar disorder, are characterized by significant neurochemical dysregulation and disturbances in biol...

Popular Online Content as a Treatment-as-Usual Control in Digital Mental Health Intervention Trials: Secondary Analysis of Two Online Randomized Controlled Trials With Repeated Measures.

BACKGROUND: Treatment-as-usual (TAU) conditions are intended to reflect the support typically received in routine treatment settings. For digital ment...

Deep learning driven clustering of post-traumatic stress disorder (PTSD) profiles in student-athletes: implications for precision and stratified mental health support.

BACKGROUND: Athletes frequently experience potentially traumatic events related to sports injuries, significantly increasing their risk of developing ...

A Comparative Evaluation of Three Large Language Models for Parent-Centered Questions About Anorexia Nervosa.

BACKGROUND: Large language models (LLMs) are increasingly used to obtain health information, including guidance on child and adolescent mental health....

Non-European migrants with schizophrenia spectrum disorders in Swiss forensic and general psychiatric care facilities - A comparative study using machine learning.

Personal history of migration poses an important risk factor for schizophrenia spectrum disorders (SSD), which are also associated with a higher rate ...

Determinants of the Perceived Ageism Index using theory-driven and data-driven approaches: evidence from the Türkiye Elderly Profile Survey 2023.

OBJECTIVES: This study examines the multidimensional determinants of perceived ageism using a combined theory- and data-driven framework based on nati...

Interpretable depressive symptoms screening via statistical reasoning-augmented large language models using wearable and environmental data.

Early assessment of depressive symptoms is essential for scalable and personalized mental health care. We developed a hybrid clinical decision support...

Multimodal artificial intelligence and online learning in youth mental health: a scoping review.

Youth mental health-related problems and disorders have garnered increased attention due to global prevalence estimates that have, in some cases, incr...

Identifying neuroimaging-based biomarkers for obsessive-compulsive disorder: A resting-state fMRI and machine learning study in patients and unaffected first-degree relatives.

BACKGROUND: Identifying whether brain alterations in obsessive-compulsive disorder (OCD) represent the illness itself or an underlying genetic vulnera...

Is it time for AI to take a leading role in mass trauma mental health response?

Machine learning (ML) and artificial intelligence (AI) offer opportunity and risk in mass trauma response, disasters and crisis. This narrative review...

Screening of molecular signatures from microRNA and mRNA expression profiling related to the efficacy of the antidepressant duloxetine and analysis of their regulatory relationship.

Previous clinical studies have reported that not all depressed patients respond to antidepressants. Therefore, finding potential predictive molecular ...

Are routinely collected clinical and sociodemographic characteristics associated with social functioning and activities of daily living in schizophrenia? A machine learning approach descriptive of a schizophrenia cohort.

Patients with schizophrenia often experience substantial impairments in social functioning and activities of daily living (ADLs). Previous studies hav...

Where next for psychiatry: its past, present and future.

Humanity is entering a new phase of social evolution with rapid digitalisation and increasing use of artificial intelligence in our lives. Psychiatric...

Development of a Contextualized, Research-Based Flemish Assessment Framework for Digital Care, Assistance, and Support: Delphi Study.

BACKGROUND: The rapid evolution of digital technologies has transformed health, mental health, and social care, offering new modalities of digital car...