Transformer-based multimodal feature enhancement networks for multimodal depression detection integrating video, audio and remote photoplethysmograph signals

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Enhancing Depression Detection Using Pretrained Multi-modal Sentiment Analysis Models with Deep Prefix Tuning

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A Lightweight Passive Depression Detection System Based on Interpretable Facial Feature Analysis

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Cross-Modal Knowledge Distillation for Depression Recognition: An Explainability Method with EEG and Pupil Area Signals

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ConvNeXt‐KAN Based Multi‐State EEG Fusion for Adolescent Unipolar Depression and Bipolar Disorder Classification

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Gradient Embedding and Modal Complementarity Networks for Audio-Video Depression Level Prediction

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MA-DLE: Speech-Based Automatic Depression Level Estimation via Memory Augmentation

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Dynamic Multi-Scale Hybrid Framework for EEG-Driven Chinese Speech Imagery

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Tensorformer-Based Multimodal Depression Detection from Concurrent Gait Patterns and Physiological Signals

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When audio-visual deep learning meets TCM facial inspection: A novel depression detection method for Chinese population

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NSANet: Non-Stationary Multi-Scale Attention Network with structured multi-task supervision for video depression detection

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Refinement Feature Fusion for Multi-model Depression DetectionPreprint

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Cross-Hierarchical Attention for Multimodal Depression DetectionPreprint

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DepAVF: An Advanced Multimodal Depression Detection Framework Using Audio-Visual Fusion and Adaptive Score Integration

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Beyond Accuracy: A Review of Model and Data Trustworthiness in Audio-Visual Depression Recognition

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MoDEpression: Exploring Individual Differences in Personalized Depression Diagnosis Using Mixture-of-Expert

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Integrating Patient History with Explainable Deep AI Using V-shaped and S-shaped Binary Protozoa Optimizer for Depression Detection

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Cross-modal Prompt Disentangled Graph Neural Networks for incomplete conversational emotion recognition

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MGFN: An Adaptive Modality-Aware Gated Fusion Network for Speech–Text Depression Detection

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IAEC-DepressNet: Identity-Adaptive and Emotionally Consistent Multimodal Depression Detection Network

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Task-Specific Aleatoric Uncertainty-Aware Multimodal Fusion for depression detection

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Image Design Feature Enhancement Method Based on Transformer and Multimodal Neural Networks

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Modelling Thematic Structure in Clinical Dialogues for Interpretable Depression Detection

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Multimodal depression and anxiety severity prediction using convolutional Kepler ResNeXt and lightweight equilibrium BLSTM explainable AI

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Multi-Modal Adaptive Fusion Transformer Network for the Estimation of Depression Level

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Cross-Hierarchical Attention for Multimodal Depression DetectionPreprint

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DPD (DePression Detection) Net: a deep neural network for multimodal depression detection

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Multimodal depression detection using a deep feature fusion network

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