Depression Detection

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6 papers in the last four weeks, down 45% on the four weeks before. 0.0% of all new papers.

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  1. Cognitive-Linguistic Indicators of Depression in Online Communities: Analysed by DistilBERT and Holographic Reduced Representation

    Apr 15, 2026Brian Van SteenDepression DetectionText Embedding Models

    School of Computing, University of Leeds

  2. Dynamic Summary Generation for Interpretable Multimodal Depression Detection

    Apr 13, 2026Shiyu Teng, Jiaqing Liu, Hao Sun +6Depression DetectionDepression Severity Estimation

    College of Information Science and Engineering, Ritsumeikan University, Shiga, Japan · College of Computer Science and Technology, Zhejiang University, Hangzhou, China · Faculty of Engineering, University of the Ryukyus, Japan

  3. Context Matters: Vision-Based Depression Detection Comparing Classical and Deep Approaches

    Apr 11, 2026Maneesh Bilalpur, Saurabh Hinduja, Sonish Sivarajkumar +4Depression DetectionDomain Generalization

    Intelligent Systems Program, University of Pittsburgh, Pittsburgh, USA · CGI Technologies and Solutions Inc, USA · University of Oregon, USA +3

  4. Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection

    Apr 11, 2026Hangbin Yu, Yudong Yang, Rongfeng Su +2Depression DetectionClinical Speech Processing

    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, China · University of Chinese Academy of Sciences · Key Laboratory of Biomedical Imaging Science and System, Chinese Academy of Sciences, China

  5. A Dual Cross-Attention Graph Learning Framework For Multimodal MRI-Based Major Depressive Disorder Detection

    Apr 11, 2026Nojod M. Alotaibi, Areej M. AlhothaliDepression DetectionMultimodal Fusion

    Department of Computer Science, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia

  6. TAAC: A gate into Trustable Audio Affective Computing

    Mar 26, 2026Xintao Hu, Feng-Qi CuiAffective ComputingDepression Detection

    Hefei University of Technology, Hefei, China

  7. When Consistency Becomes Bias: Interviewer Effects in Semi-Structured Clinical Interviews

    Mar 25, 2026Hasindri Watawana, Sergio Burdisso, Diego A. Moreno-Galván +4Depression DetectionInterpretable ML

    Idiap Research Institute, Switzerland · EPFL, Switzerland · Centro de Investigación en Matemáticas (CIMAT), Mexico +1

  8. Fusion Learning from Dynamic Functional Connectivity: Combining the Amplitude and Phase of fMRI Signals to Identify Brain Disorders

    Mar 14, 2026Jinlong Hu, Jiatong Huang, Zijian CaiFunctional ConnectivityNeuroimaging

    Guangdong Provincial Key Laboratory of Multimodal Big Data Intelligent Analysis, School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

  9. IDRL: An Individual-Aware Multimodal Depression-Related Representation Learning Framework for Depression Diagnosis

    Mar 12, 2026Chongxiao Wang, Junjie Liang, Peng Cao +2Depression DetectionMultimodal Fusion

    School of Computer Science and Engineering, Northeastern University, Shenyang, China · Key Laboratory of Intelligent Computing in Medical Image of Ministry of Education, Northeastern University, Shenyang, China · National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang, China +1

  10. Depression Detection at the Point of Care: Automated Analysis of Linguistic Signals from Routine Primary Care Encounters

    Mar 11, 2026Feng Chen, Manas Bedmutha, Janice Sabin +3Depression DetectionClinical NLP

    University of Washington, Seattle, WA · University of California San Diego, La Jolla, CA

  11. Bias and Fairness in Self-Supervised Acoustic Representations for Cognitive Impairment Detection

    Mar 3, 2026Kashaf Gulzar, Korbinian Riedhammer, Elmar Nöth +2Speech-Based Dementia DetectionClinical Speech Processing

    Zentrum für Künstliche Intelligenz (KIZ), Technische Hochschule Nürnberg, Nürnberg, Germany · Pattern Recognition Lab, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany

  12. CRCC: Contrast-Based Robust Cross-Subject and Cross-Site Representation Learning for EEG

    Feb 22, 2026Xiaobin Wong, Zhonghua Zhao, Haoran Guo +5Cross-Dataset GeneralizationCross-Domain Generalization

    Tsinghua Laboratory of Brain and Intelligence · Institute of Automation, Chinese Academy of Sciences · University of Chinese Academy of Sciences +6

  13. "Mirror" Large Language Model Evaluations of Depression are Criterion Contaminated

    Aug 7, 2025Tong Li, Rasiq Hussain, Mehak Gupta +1Depression DetectionMental Health

    Division of Computational & Data Sciences (DCDS), Washington University in St. Louis, St. Louis, MO · Department of Computer Science, SMU · Department of Psychological & Brain Sciences, Washington University in St. Louis