Psychiatry

Development of a short form of the Geriatric Depression Scale-30 based on item response theory and the RiskSLIM algorithm.

Recently, methods of quickly and accurately screening for geriatric depression have attracted substa...

Multi-modal cross-domain self-supervised pre-training for fMRI and EEG fusion.

Neuroimaging techniques including functional magnetic resonance imaging (fMRI) and electroencephalog...

Objective approach to diagnosing attention deficit hyperactivity disorder by using pixel subtraction and machine learning classification of outpatient consultation videos.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) is a common childhood neurodevelopmental...

MCBERT: A multi-modal framework for the diagnosis of autism spectrum disorder.

Within the domain of neurodevelopmental disorders, autism spectrum disorder (ASD) emerges as a disti...

Exploring correlates of high psychiatric inpatient utilization in Switzerland: a descriptive and machine learning analysis.

BACKGROUND: This study investigated socio-demographic, psychiatric, and psychological characteristic...

Momentary Depression Severity Prediction in Patients With Acute Depression Who Undergo Sleep Deprivation Therapy: Speech-Based Machine Learning Approach.

BACKGROUND: Mobile devices for remote monitoring are inevitable tools to support treatment and patie...

Machine learning analysis of factors affecting college students' academic performance.

This study aims to explore various key factors influencing the academic performance of college stude...

Anxiety about artificial intelligence from patient and doctor-physician.

OBJECTIVE: This paper investigates the anxiety surrounding the integration of artificial intelligenc...

Pre-trained artificial intelligence language model represents pragmatic language variability central to autism and genetically related phenotypes.

Many individuals with autism experience challenges using language in social contexts (i.e., pragmati...

Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study.

BACKGROUND: Digital mental health is a promising paradigm for individualized, patient-driven health ...

How do machine learning models perform in the detection of depression, anxiety, and stress among undergraduate students? A systematic review.

Undergraduate students are often impacted by depression, anxiety, and stress. In this context, machi...

Digital phenotyping from wearables using AI characterizes psychiatric disorders and identifies genetic associations.

Psychiatric disorders are influenced by genetic and environmental factors. However, their study is h...

Multimodal autism detection: Deep hybrid model with improved feature level fusion.

OBJECTIVE: Social communication difficulties are a characteristic of autism spectrum disorder (ASD),...

Auxiliary identification of depression patients using interpretable machine learning models based on heart rate variability: a retrospective study.

OBJECTIVE: Depression has emerged as a global public health concern with high incidence and disabili...

Comparison between clinician and machine learning prediction in a randomized controlled trial for nonsuicidal self-injury.

BACKGROUND: Nonsuicidal self-injury is a common health problem in adolescents and associated with fu...

Evaluating virtual reality technology in psychotherapy: impacts on anxiety, depression, and ADHD.

BACKGROUND: Mental health issues pose a significant challenge for medical providers and the general ...

Real-time assistance in suicide prevention helplines using a deep learning-based recommender system: A randomized controlled trial.

OBJECTIVE: To evaluate the effectiveness and usability of an AI-assisted tool in providing real-time...

Immune-based Machine learning Prediction of Diagnosis and Illness State in schizophrenia and bipolar Disorder: How data bias and overfitting were avoided.

In a letter critiquing our manuscript, Takefuji highlights general pitfalls in machine learning, wit...

Artificial intelligence in mental healthcare: transformative potential vs. the necessity of human interaction.

Artificial Intelligence and Its Revolutionary Role in Physical and Mental Rehabilitation: A Review of Recent Advancements.

The integration of artificial intelligence (AI) technologies into physical and mental rehabilitation...

Identification of autism spectrum disorder using electroencephalography and machine learning: a review.

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition characterized by communication barr...