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IIFDD: Intra and inter-modal fusion for depression detection with multi-modal information from Internet of Medical Things
16 references·2 citing·54 second hop
IIFDD: Intra and inter-modal fusion for depression detection with multi-modal information from Internet of Medical Things (2023)IIFDD: Intra and inter-modal fusion for d…CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation (2022)CubeMLP: An MLP-based Model f…Automatic Depression Detection: an Emotional Audio-Textual Corpus and A Gru/Bilstm-Based Model (2022)Automatic Depression Detectio…Progressive Modality Reinforcement for Human Multimodal Emotion Recognition from Unaligned Multimodal Sequences (2021)Progressive Modality Reinforc…MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech (2021)MFCC-based Recurrent Neural N…Audio based depression detection using Convolutional Autoencoder (2021)Audio based depression detect…A textual-based featuring approach for depression detection using machine learning classifiers and social media texts (2021)A textual-based featuring app…Machine Learning-Based Approach for Depression Detection in Twitter Using Content and Activity Features (2020)Machine Learning-Based Approa…AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition (2019)AVEC 2019 Workshop and Challe…A text classification framework for simple and effective early depression detection over social media streams (2019)A text classification framewo…Psychometric properties and clinical utility of brief measures of depression, anxiety, and general distress: The PHQ-2, GAD-2, and K-6 (2018)Psychometric properties and c…Topic Modeling Based Multi-modal Depression Detection (2017)Topic Modeling Based Multi-mo…Depression and Self-Harm Risk Assessment in Online Forums (2017)Depression and Self-Harm Risk…Automatic Assessment of Depression Based on Visual Cues: A Systematic Review (2017)Automatic Assessment of Depre…The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing (2015)The Geneva Minimalistic Acous…Detecting Depression Severity from Vocal Prosody (2013)Detecting Depression Severity…Facial Action Coding System (1978)Facial Action Coding SystemEnhancing Emotional Well-Being With IoT Data Solutions for Depression: A Systematic Review (2025)Enhancing Emotional Well-Bein…Classification and severity assessment of disaster losses based on multi-modal information in social media (2025)Classification and severity a…A RATING SCALE FOR DEPRESSION (1960)Prevalence, Severity, and Comorbidity of 12-Month DSM-IV Disorders in the National Comorbidity Survey Replication (2005)Diagnostic and Statistical Manual of Mental Disorders (2013)Automated Depression Diagnosis Based on Deep Networks to Encode Facial Appearance and Dynamics (2017)Automated depression analysis using convolutional neural networks from speech (2018)Visually Interpretable Representation Learning for Depression Recognition from Facial Images (2018)Acoustic profiles in vocal emotion expression. 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References

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  • 2015The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing1,815 cited
  • 2019AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition407 cited
  • 2018Psychometric properties and clinical utility of brief measures of depression, anxiety, and general distress: The PHQ-2, GAD-2, and K-6401 cited
  • 2017Depression and Self-Harm Risk Assessment in Online Forums338 cited
  • 2021MFCC-based Recurrent Neural Network for automatic clinical depression recognition and assessment from speech290 cited
  • 2013Detecting Depression Severity from Vocal Prosody278 cited
  • 2021A textual-based featuring approach for depression detection using machine learning classifiers and social media texts231 cited
  • 2017Automatic Assessment of Depression Based on Visual Cues: A Systematic Review228 cited
  • 2021Progressive Modality Reinforcement for Human Multimodal Emotion Recognition from Unaligned Multimodal Sequences221 cited
  • 2019A text classification framework for simple and effective early depression detection over social media streams216 cited
  • 2022Automatic Depression Detection: an Emotional Audio-Textual Corpus and A Gru/Bilstm-Based Model201 cited
  • 2020Machine Learning-Based Approach for Depression Detection in Twitter Using Content and Activity Features193 cited

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  • 2022CubeMLP: An MLP-based Model for Multimodal Sentiment Analysis and Depression Estimation174 cited
  • 2017Topic Modeling Based Multi-modal Depression Detection155 cited
  • 2021Audio based depression detection using Convolutional Autoencoder150 cited
  • Cited by

    • 2025Classification and severity assessment of disaster losses based on multi-modal information in social media14 cited
    • 2025Enhancing Emotional Well-Being With IoT Data Solutions for Depression: A Systematic Review4 cited