Psychiatry

Automating multi-label crisis detection in psychological support hotlines with pre-trained models.

Psychological support hotlines provide immediate help to individuals in crisis, with operators asses...

AI-driven multimodal simulation for psychiatric clinical education: conceptual framework and preliminary validation of the cognitive core.

BACKGROUND: The global shortage of psychiatrists limits learners' exposure to authentic patient enco...

Quality of Autism Information Generated by Artificial Intelligence Tools: Implications for Paediatric Care.

AIM: Families increasingly turn to artificial intelligence (AI) tools for information about autism s...

Developing a Clinical Prediction Model for Nonimprovement of Depressive Symptoms at Discharge After Treatment of Eating Disorders.

OBJECTIVE: Depressive symptoms are highly prevalent among people with eating disorders (ED). Althoug...

Self-Identified Age Cohorts and Personal Experience Sharing in Pseudonymous Online Spaces: Natural Language Processing Analysis of Reddit.

BACKGROUND: While older adults' social media use has been widely studied for its instrumental benefi...

Who Is Getting the Help They Need? An AI-Driven Study of Intersectional Disparities in Mental Health Service Utilization Among Young Adults with Suicidal Ideation.

Despite the critical role of mental health services in suicide prevention, disparities in service ut...

Digital patient education and its role in overcoming dental anxiety and barriers to endodontic care.

Dental fear and anxiety (DFA) serve as a significant obstacle to oral healthcare, affecting approxim...

Explaining sleep disorders in children after earthquakes using SHAP modelling: Container City modelling.

BACKGROUND: It is well-known that sleep disturbances and sleep-related traumas are the most common s...

Role of artificial intelligence in analyzing human behavior and predicting personality traits and personality disorders.

Traditional approaches to the diagnosis of personality disorders, including a clinical interview and...

Structural imaging predictors of ketamine response in treatment-resistant depression: a machine learning approach.

Ketamine has demonstrated rapid antidepressant efficacy in treatment-resistant depression (TRD), but...

Comparing machine and deep learning models for pediatric anxiety classification using structured EHRs and area-based measures of health data.

OBJECTIVE: This retrospective, case-control study with internal validation evaluates the performance...

Adaptive drift-aware multi-stage deep learning framework for EEG-based schizophrenia diagnosis.

This study introduces a novel adaptive deep learning framework for EEG-based schizophrenia diagnosis...

Using natural language processing to assess proxy measures of therapeutic alliance across suicide risk tiers.

Therapeutic alliance is a core predictor of psychotherapeutic outcome, in general, and suicide preve...

Artificial Intelligence Centrality in Psychotic Delusions and Violence Risk in Forensic Psychiatry: Observational Study of Judicial Decisions.

BACKGROUND: Artificial intelligence (AI)-themed delusions are increasingly observed in psychotic-spe...

Machine learning-based differentiation of major depressive disorder and bipolar disorder using entropy-derived EEG biomarkers in drug-naïve patients.

Sustainable ectoine production: microbial fermentation, recombinant biosynthesis, downstream processing, and AI-driven process optimization.

Ectoine, a bioactive molecule, has gained significant attention in industrial applications due to it...

Classifying ADHD Presentations Using Temporally Segmented Behavioral Data from a Serious Game.

Distinguishing attention deficit/hyperactivity disorder (ADHD) presentations, such as predominantly ...

Combining Machine Learning Models and Screening to Enhance Suicide Risk Identification for American Indian Patients: Retrospective Cohort Study.

BACKGROUND: American Indian and Alaska Native communities experience disproportionately high suicide...

Contribution of Longitudinal Mobile Health Measures in the Dynamic Track of Patients With Major Depressive Disorder: Multiple Centers, Prospective Cohort Study Using Functional Data Analysis and Machine Learning.

BACKGROUND: Continuous follow-up for patients with major depressive disorder (MDD) is essential for ...

The Quality and Characteristics of Digital Mental Health Apps: Mixed Methods Study.

BACKGROUND: There are around 20,000 mental health apps available in app stores. The Organisation for...

Predicting depressive and anxiety symptoms among Lebanese and Syrian adults in a suburb of Beirut, Lebanon, during concurrent crises: nested cross-sectional study.

OBJECTIVE: This study aimed to develop prediction models for symptoms of poor mental health among Le...