Psychiatry

Depression

Latest AI and machine learning research in depression for healthcare professionals.

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A psychologically interpretable artificial intelligence framework for the screening of loneliness, depression, and anxiety.

Negative emotions such as loneliness, depression, and anxiety (LDA) are prevalent and pose significa...

Feb 2025 39697049
Identification of Depression Subtypes in Parkinson's Disease Patients via Structural MRI Whole-Brain Radiomics: An Unsupervised Machine Learning Study.

OBJECTIVE: Current clinical evaluation may tend to lack precision in detecting depression in Parkins...

Feb 2025 39915918
Digital Health Innovations for Screening and Mitigating Mental Health Impacts of Adverse Childhood Experiences: Narrative Review

This study presents a narrative review of the use of digital health technologies (DHTs) and artifi...

Machine Learning Fairness for Depression Detection using EEG Data

This paper presents the very first attempt to evaluate machine learning fairness for depression de...

LLM Assistance for Pediatric Depression

Traditional depression screening methods, such as the PHQ-9, are particularly challenging for chil...

Towards Explainable Multimodal Depression Recognition for Clinical Interviews

Recently, multimodal depression recognition for clinical interviews (MDRC) has recently attracted ...

(1)
Breaking the Stigma! Unobtrusively Probe Symptoms in Depression Disorder Diagnosis Dialogue

Stigma has emerged as one of the major obstacles to effectively diagnosing depression, as it preve...

Salvaging Forbidden Treasure in Medical Data: Utilizing Surrogate Outcomes and Single Records for Rare Event Modeling

The vast repositories of Electronic Health Records (EHR) and medical claims hold untapped potentia...

DepressionX: Knowledge Infused Residual Attention for Explainable Depression Severity Assessment

In today's interconnected society, social media platforms have become an important part of our liv...

U-Fair: Uncertainty-based Multimodal Multitask Learning for Fairer Depression Detection

Machine learning bias in mental health is becoming an increasingly pertinent challenge. Despite pr...

Enhanced Large Language Models for Effective Screening of Depression and Anxiety

Depressive and anxiety disorders are widespread, necessitating timely identification and managemen...

(1)
Investigating Large Language Models in Inferring Personality Traits from User Conversations

Large Language Models (LLMs) are demonstrating remarkable human like capabilities across diverse d...

Motif Discovery Framework for Psychiatric EEG Data Classification

In current medical practice, patients undergoing depression treatment must wait four to six weeks ...

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

This study introduces LlaMADRS, a novel framework leveraging open-source Large Language Models (LL...

Neural Timescale of Adolescents Major Depressive Disorder

Adolescent major depressive disorder (MDD) is characterized by heterogeneous symptomatology and comp...

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