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Context-aware Deep Learning for Multi-modal Depression Detection

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References

2010Validation of PHQ-2 and PHQ-9 to Screen for Major Depression in the Primary Care Population1,278 cited
2014The Distress Analysis Interview Corpus of human and computer interviews591 cited
2018Detecting Depression with Audio/Text Sequence Modeling of Interviews350 cited
2016DepAudioNet299 cited
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2006Should we screen for depression?195 cited
2017Multimodal Measurement of Depression Using Deep Learning Models175 cited
2016Decision Tree Based Depression Classification from Audio Video and Language Information148 cited

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2022Depression Detection Based on Hybrid Deep Learning SSCL Framework Using Self-Attention Mechanism: An Application to Social Networking Data82 cited
2021HCAG: A Hierarchical Context-Aware Graph Attention Model for Depression Detection79 cited
2020Hybrid CNN-SVM classifier for efficient depression detection system

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73 cited

2023Spatial–Temporal Feature Network for Speech-Based Depression Recognition73 cited

2024Context-aware prediction of active and passive user engagement: Evidence from a large online social platform12 cited

2025ICT Adoption in Education: Unveiling Emergency Remote Teaching Challenges for Students with Functional Diversity Through Topic Identification in Modern Greek Data1 cited