Psychiatry

[Construction of recognition models for subthreshold depression based on multiple machine learning algorithms and vocal emotional characteristics].

OBJECTIVES: To construct vocal recognition classification models using 6 machine learning algorithms and vocal emotional characteristics of individuals with subthreshold depression to facilitate early identification of subthreshold depression.

Wearable-Derived Behavioral and Physiological Biomarkers for Classifying Unipolar and Bipolar Depression Severity

Depression is a complex mental disorder characterized by a diverse range of observable and measurable indicators that go beyond traditional subjective assessments. Recent research has increasingly focused on objective, passive, and continuous monitoring using wearable devices to gain more precise insights into the physiological and behavioral aspects of depression. However, most existing studies...

Interpersonal Theory of Suicide as a Lens to Examine Suicidal Ideation in Online Spaces

Suicide is a critical global public health issue, with millions experiencing suicidal ideation (SI) each year. Online spaces enable individuals to e...

Thousand Voices of Trauma: A Large-Scale Synthetic Dataset for Modeling Prolonged Exposure Therapy Conversations

The advancement of AI systems for mental health support is hindered by limited access to therapeutic conversation data, particularly for trauma trea...

Mirror: Multimodal Cognitive Reframing Therapy for Rolling with Resistance

Recent studies have explored the use of large language models (LLMs) in psychotherapy; however, text-based cognitive behavioral therapy (CBT) models...

Leveraging Large Language Models for Multi-Class and Multi-Label Detection of Drug Use and Overdose Symptoms on Social Media

Drug overdose remains a critical global health issue, often driven by misuse of opioids, painkillers, and psychiatric medications. Traditional resea...

"It Listens Better Than My Therapist": Exploring Social Media Discourse on LLMs as Mental Health Tool

The emergence of generative AI chatbots such as ChatGPT has prompted growing public and academic interest in their role as informal mental health su...

VR MRI Training for Adolescents: A Comparative Study of Gamified VR, Passive VR, 360 Video, and Traditional Educational Video

Magnetic Resonance Imaging (MRI) can be a stressful experience for pediatric patients due to the loud acoustic environment, enclosed scanner bore, a...

EmoAgent: Assessing and Safeguarding Human-AI Interaction for Mental Health Safety

The rise of LLM-driven AI characters raises safety concerns, particularly for vulnerable human users with psychological disorders. To address these ...

Comorbidity-Informed Transfer Learning for Neuro-developmental Disorder Diagnosis

Neuro-developmental disorders are manifested as dysfunctions in cognition, communication, behaviour and adaptability, and deep learning-based comput...

Local Temporal Feature Enhanced Transformer with ROI-rank Based Masking for Diagnosis of ADHD

In modern society, Attention-Deficit/Hyperactivity Disorder (ADHD) is one of the common mental diseases discovered not only in children but also in ...

Linguistic Comparison of AI- and Human-Written Responses to Online Mental Health Queries

The ubiquity and widespread use of digital and online technologies have transformed mental health support, with online mental health communities (OM...

A Confounding Factors-Inhibition Adversarial Learning Framework for Multi-site fMRI Mental Disorder Identification

In open data sets of functional magnetic resonance imaging (fMRI), the heterogeneity of the data is typically attributed to a combination of factors...

Leveraging Large Language Models for Cost-Effective, Multilingual Depression Detection and Severity Assessment

Depression is a prevalent mental health disorder that is difficult to detect early due to subjective symptom assessments. Recent advancements in lar...

MedGNN: Capturing the Links Between Urban Characteristics and Medical Prescriptions

Understanding how urban socio-demographic and environmental factors relate with health is essential for public health and urban planning. However, t...

Classification of ADHD and Healthy Children Using EEG Based Multi-Band Spatial Features Enhancement

Attention Deficit Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder in children, characterized by difficulties in attention, hyp...

Measuring Mental Health Variables in Computational Research: Toward Validated, Dimensional, and Transdiagnostic Approaches

Computational mental health research develops models to predict and understand psychological phenomena, but often relies on inappropriate measures o...

Improving Brain Disorder Diagnosis with Advanced Brain Function Representation and Kolmogorov-Arnold Networks

Quantifying functional connectivity (FC), a vital metric for the diagnosis of various brain disorders, traditionally relies on the use of a pre-defi...

Machine learning reveals connections between preclinical type 2 diabetes subtypes and brain health.

Previous research has established type 2 diabetes mellitus as a significant risk factor for various disorders, adversely impacting human health. While...

OnRL-RAG: Real-Time Personalized Mental Health Dialogue System

Large language models (LLMs) have been widely used for various tasks and applications. However, LLMs and fine-tuning are limited to the pre-trained ...