Psychiatry

ASA-ED: Automated Stress Assessment Via Emotion-Awareness-Driven Deep Hybrid Learning Fusing MTF and RP.

Currently, most studies on mental stress evaluation mainly focus on classification tasks, while research on accurately estimating continuous stress levels using deep learning for early identification remains limited. This study proposes an end-to-end continuous stress assessment framework based on a deep hybrid learning architecture. The framework employs efficient channel attention convolution to...

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 symptoms experienced by children following a traumatic event. Our study aims to predict the factors affecting post-traumatic sleep disorders in children living in container cities by using machine learning models. METHODS: This descriptive, cross-sectional study determined the average age of the chil...

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 a self-report, are usually limited by subjectivit...

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 clinical decision-making is challenging due to va...

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 of machine learning (ML) and deep learning (DL) m...

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 that addresses the limitations of existing static...

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 prevention, specifically. Although clinical literature ...

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-spectrum disorders, reflecting the incorporation of c...

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 its exceptional stabilizing properties. This natural...

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

Distinguishing attention deficit/hyperactivity disorder (ADHD) presentations, such as predominantly inattentive (ADHD-I) and hyperactive/impulsive (AD...

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 rates. While machine learning (ML) models leverag...

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 treatment decisions and a better prognosis. There ...

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 the Review of Care and Health Apps (ORCHA), a Uni...

Grief in the Digital Age: A Bibliometric Exploration of Technology-Mediated Bereavement Support.

The present study aims to examine the existing body of research on technology-mediated bereavement support through a bibliometric analysis, employing ...

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 Lebanese adults and adult Syrian refugees or migrant...

Using the Novel Translation Validity Index to Evaluate GenAI Translations of the Patient Health Questionnaire-9 Into Nine Languages.

Background and Purpose: Depressive symptoms affect 280 million people worldwide. Although generative artificial intelligence (GenAI) tools are increas...

ADHD identification from real-life recorded video.

Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder that affects more than 10% of the population. Accurate and early diag...

Offspring genetic diversity regulates rearing experiences that predict differential susceptibility to Chd8 haploinsufficiency.

Loss-of-function mutations in the autism-associated CHD8 gene are highly penetrant for trait and behavioral abnormalities in children, but there is su...

Construction of a prediction model for depression risk in elderly patients with chronic obstructive pulmonary disease based on machine learning algorithms and analysis of influencing factors.

Patients with chronic obstructive pulmonary disease (COPD) are at a high risk of depression, which not only accelerates disease progression but also s...