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Depression Detection

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Showing 51–100 of 157 papers

TitleStatusHype
Deep Knowledge-Infusion For Explainable Depression Detection—0
Density Adaptive Attention-based Speech Network: Enhancing Feature Understanding for Mental Health Disorders—0
Multimodal Gender Fairness in Depression Prediction: Insights on Data from the USA & China—0
NarrationDep: Narratives on Social Media For Automatic Depression Detection—0
They Look Like Each Other: Case-based Reasoning for Explainable Depression Detection on Twitter using Large Language Models—0
Heterogeneous Subgraph Network with Prompt Learning for Interpretable Depression Detection on Social Media—0
Depression Detection and Analysis using Large Language Models on Textual and Audio-Visual Modalities—0
A Depression Detection Method Based on Multi-Modal Feature Fusion Using Cross-Attention—0
Predicting Individual Depression Symptoms from Acoustic Features During Speech—0
We Care: Multimodal Depression Detection and Knowledge Infused Mental Health Therapeutic Response Generation—0
Underneath the Numbers: Quantitative and Qualitative Gender Fairness in LLMs for Depression Prediction—0
ComFeAT: Combination of Neural and Spectral Features for Improved Depression Detection—0
Multi-Explainable TemporalNet: An Interpretable Multimodal Approach using Temporal Convolutional Network for User-level Depression Detection—0
Multi Class Depression Detection Through Tweets using Artificial IntelligenceCode0
Test-Time Training for Depression Detection—0
Assessing ML Classification Algorithms and NLP Techniques for Depression Detection: An Experimental Case Study—0
Diverse Perspectives, Divergent Models: Cross-Cultural Evaluation of Depression Detection on Twitter—0
MOGAM: A Multimodal Object-oriented Graph Attention Model for Depression Detection—0
Depression Detection on Social Media with Large Language Models—0
Enhancing Depression-Diagnosis-Oriented Chat with Psychological State Tracking—0
A Privacy-Preserving Unsupervised Speaker Disentanglement Method for Depression Detection from SpeechCode0
MoodCapture: Depression Detection Using In-the-Wild Smartphone Images—0
When LLMs Meets Acoustic Landmarks: An Efficient Approach to Integrate Speech into Large Language Models for Depression Detection—0
Illuminate: A novel approach for depression detection with explainable analysis and proactive therapy using prompt engineering—0
Data Quality Matters: Suicide Intention Detection on Social Media Posts Using RoBERTa-CNN—0
Detecting mental disorder on social media: a ChatGPT-augmented explainable approachCode0
Few-Shot Learning for Chronic Disease Management: Leveraging Large Language Models and Multi-Prompt Engineering with Medical Knowledge Injection—0
Harnessing Large Language Models Over Transformer Models for Detecting Bengali Depressive Social Media Text: A Comprehensive StudyCode0
CANAMRF: An Attention-Based Model for Multimodal Depression Detection—0
DeepLearningBrasil@LT-EDI-2023: Exploring Deep Learning Techniques for Detecting Depression in Social Media TextCode0
Early Detection of Depression and Eating Disorders in Spanish: UNSL at MentalRiskES 2023—0
Using Audio Data to Facilitate Depression Risk Assessment in Primary Health Care—0
Transferring speech-generic and depression-specific knowledge for Alzheimer's disease detection—0
Hierarchical attention interpretation: an interpretable speech-level transformer for bi-modal depression detection—0
DepreSym: A Depression Symptom Annotated Corpus and the Role of LLMs as Assessors of Psychological Markers—0
Explainable Depression Detection via Head Motion Patterns—0
The Relationship Between Speech Features Changes When You Get Depressed: Feature Correlations for Improving Speed and Performance of Depression Detection—0
A Cost-aware Study of Depression Language on Social Media using Topic and Affect Contextualization—0
A Framework for Identifying Depression on Social Media: MentalRiskES@IberLEF 2023Code0
Detect Depression from Social Networks with Sentiment Knowledge Sharing—0
Self-supervised representations in speech-based depression detection—0
What Symptoms and How Long? An Interpretable AI Approach for Depression Detection in Social Media—0
Dynamic Graph Representation Learning for Depression Screening with Transformer—0
Read, Diagnose and Chat: Towards Explainable and Interactive LLMs-Augmented Depression Detection in Social Media—0
Detection of depression on social networks using transformers and ensemblesCode0
Evaluation of ChatGPT for NLP-based Mental Health Applications—0
Depression detection in social media posts using affective and social norm features—0
Transfer Learning for Real-time Deployment of a Screening Tool for Depression Detection Using Actigraphy—0
Depression Detection Using Digital Traces on Social Media: A Knowledge-aware Deep Learning Approach—0
Handwriting and Drawing for Depression Detection: A Preliminary Study—0
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