Psychiatry

Enhanced Large Language Models for Effective Screening of Depression and Anxiety

Depressive and anxiety disorders are widespread, necessitating timely identification and management. Recent advances in Large Language Models (LLMs) offer potential solutions, yet high costs and ethical concerns about training data remain challenges. This paper introduces a pipeline for synthesizing clinical interviews, resulting in 1,157 interactive dialogues (PsyInterview), and presents EmoSca...

Deep Learning-Based Feature Fusion for Emotion Analysis and Suicide Risk Differentiation in Chinese Psychological Support Hotlines

Mental health is a critical global public health issue, and psychological support hotlines play a pivotal role in providing mental health assistance and identifying suicide risks at an early stage. However, the emotional expressions conveyed during these calls remain underexplored in current research. This study introduces a method that combines pitch acoustic features with deep learning-based f...

Large Language Models for Interpretable Mental Health Diagnosis

We propose a clinical decision support system (CDSS) for mental health diagnosis that combines the strengths of large language models (LLMs) and con...

Investigating Large Language Models in Inferring Personality Traits from User Conversations

Large Language Models (LLMs) are demonstrating remarkable human like capabilities across diverse domains, including psychological assessment. This s...

From Conversation to Automation: Leveraging LLMs for Problem-Solving Therapy Analysis

Problem-solving therapy (PST) is a structured psychological approach that helps individuals manage stress and resolve personal issues by guiding the...

Motif Discovery Framework for Psychiatric EEG Data Classification

In current medical practice, patients undergoing depression treatment must wait four to six weeks before a clinician can assess medication response ...

MADUV: The 1st INTERSPEECH Mice Autism Detection via Ultrasound Vocalization Challenge

The Mice Autism Detection via Ultrasound Vocalization (MADUV) Challenge introduces the first INTERSPEECH challenge focused on detecting autism spect...

LlaMADRS: Prompting Large Language Models for Interview-Based Depression Assessment

This study introduces LlaMADRS, a novel framework leveraging open-source Large Language Models (LLMs) to automate depression severity assessment usi...

Sentiment-guided Commonsense-aware Response Generation for Mental Health Counseling

The crisis of mental health issues is escalating. Effective counseling serves as a critical lifeline for individuals suffering from conditions like ...

A Study about Distribution and Acceptance of Conversational Agents for Mental Health in Germany: Keep the Human in the Loop?

Good mental health enables individuals to cope with the normal stresses of life. In Germany, approximately one-quarter of the adult population is af...

Gaze Behavior During a Long-Term, In-Home, Social Robot Intervention for Children with ASD

Atypical gaze behavior is a diagnostic hallmark of Autism Spectrum Disorder (ASD), playing a substantial role in the social and communicative challe...

PSYCHE: A Multi-faceted Patient Simulation Framework for Evaluation of Psychiatric Assessment Conversational Agents

Recent advances in large language models (LLMs) have accelerated the development of conversational agents capable of generating human-like responses...

Large Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case

Large language models (LLMs) are increasingly attracting the attention of healthcare professionals for their potential to assist in diagnostic asses...

Empirical Analysis of Nature-Inspired Algorithms for Autism Spectrum Disorder Detection Using 3D Video Dataset

Autism Spectrum Disorder (ASD) is a chronic neurodevelopmental disorder symptoms of which includes repetitive behaviour and lack of social and commu...

Are LLMs effective psychological assessors? Leveraging adaptive RAG for interpretable mental health screening through psychometric practice

In psychological practice, standardized questionnaires serve as essential tools for assessing mental constructs (e.g., attitudes, traits, and emotio...

Deformed Probability Estimation in Goal-Directed reinforcement learning model explains anxious-depression dimensions of psychiatric disorders

Psychiatric disorders are complex, multi-dimensional pathologies rooted in diverse cognitive processes. Computational psychiatry aims to reveal distor...

Multi-task machine learning reveals the functional neuroanatomy fingerprint of mental processing

Mental processing delineates the functions of human mind encompassing a wide range of motor, sensory, emotional, and cognitive processes, each of whic...

Neural Timescale of Adolescents Major Depressive Disorder

Adolescent major depressive disorder (MDD) is characterized by heterogeneous symptomatology and complex neurodevelopmental underpinnings. Here, we inv...

Accurate and Interpretable Prediction of Antidepressant Treatment Response from Receptor-informed Neuroimaging

Conventional antidepressants show moderate efficacy in treating major depressive disorder. Psychedelic-assisted therapy holds promise, yet individual ...

dFCExpert: Learning Dynamic Functional Connectivity Patterns with Modularity and State Experts

Characterizing brain dynamic functional connectivity (dFC) patterns from functional Magnetic Resonance Imaging (fMRI) data is of paramount importance ...