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Depression Detection

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Showing 51–75 of 157 papers

TitleStatusHype
Depression Detection Using Digital Traces on Social Media: A Knowledge-aware Deep Learning Approach—0
Explainable Depression Detection with Multi-Modalities Using a Hybrid Deep Learning Model on Social Media—0
DepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media—0
Depression Symptoms Modelling from Social Media Text: A Semi-supervised Learning Approach—0
DepreSym: A Depression Symptom Annotated Corpus and the Role of LLMs as Assessors of Psychological Markers—0
Detect Depression from Social Networks with Sentiment Knowledge Sharing—0
Detecting Depression in Social Media using Fine-Grained Emotions—0
Detecting Early Onset of Depression from Social Media Text using Learned Confidence Scores—0
Depression Detection on Social Media with Large Language Models—0
Avengers Assemble: Amalgamation of Non-Semantic Features for Depression Detection—0
Depression detection in social media posts using transformer-based models and auxiliary features—0
Depression detection in social media posts using affective and social norm features—0
Automatic Depression Detection via Learning and Fusing Features from Visual Cues—0
A Multitask Deep Learning Approach for User Depression Detection on Sina Weibo—0
A Depression Detection Method Based on Multi-Modal Feature Fusion Using Cross-Attention—0
A BERT-Based Summarization approach for depression detection—0
Depression detection from Social Media Bangla Text Using Recurrent Neural Networks—0
Depression Detection and Analysis using Large Language Models on Textual and Audio-Visual Modalities—0
Density Adaptive Attention-based Speech Network: Enhancing Feature Understanding for Mental Health Disorders—0
Automated speech-based screening of depression using deep convolutional neural networks—0
A Linguistically-Informed Fusion Approach for Multimodal Depression Detection—0
Deep Temporal Modelling of Clinical Depression through Social Media Text—0
Deep Depression Prediction on Longitudinal Data via Joint Anomaly Ranking and Classification—0
Auto-Landmark: Acoustic Landmark Dataset and Open-Source Toolkit for Landmark Extraction—0
Deep Learning for Depression Recognition with Audiovisual Cues: A Review—0
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