mlsanityData to 7 Oct 2026

Symptom Identification for Interpretable Detection of Multiple Mental Disorders

arXiv 2205.11308 ↗First posted 23 May 2022cs.CLcited by 20

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Abstract (arXiv)

Mental disease detection (MDD) from social media has suffered from poor generalizability and interpretability, due to lack of symptom modeling. This paper introduces PsySym, the first annotated symptom identification corpus of multiple psychiatric disorders, to facilitate further research progress. PsySym is annotated according to a knowledge graph of the 38 symptom classes related to 7 mental diseases complied from established clinical manuals and scales, and a novel annotation framework for diversity and quality. Experiments show that symptom-assisted MDD enabled by PsySym can outperform strong pure-text baselines. We also exhibit the convincing MDD explanations provided by symptom predictions with case studies, and point to their further potential applications.

Key facts. Cited by 20 papers in the map (data through 7 Oct 2026). Builds on 19 of its 43 references that are in the map. First posted on arXiv 23 May 2022.

Builds on

19 of 43 references.

References · 19

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7 more
  1. 2021Embracing Ambiguity: Shifting the Training Target of NLI Modelscited by 22
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 4; 2024: 3; 2025: 7; 2026: 5.

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  1. 2024Large Language Models in Mental Health Care: a Scoping Reviewcited by 34
  2. 2023LLM-empowered Chatbots for Psychiatrist and Patient Simulation: Application and Evaluationcited by 33
  3. 2023Explainable Depression Symptom Detection in Social Mediacited by 9
  4. 2024A Comprehensive Evaluation of Large Language Models on Mental Illnessescited by 7
  5. 2024On the State of NLP Approaches to Modeling Depression in Social Media: A Post-COVID-19 Outlookcited by 6
  6. 2022Semantic Similarity Models for Depression Severity Estimationcited by 5
  7. 2023Utilizing ChatGPT Generated Data to Retrieve Depression Symptoms from Social Mediacited by 5
  8. 2025Labeling Free-text Data using Language Model Ensemblescited by 5
  9. 2025Datasets for Depression Modeling in Social Media: An Overviewcited by 5
  10. 2023A Simple and Flexible Modeling for Mental Disorder Detection by Learning from Clinical Questionnairescited by 4
  11. 2025Detecting Early and Implicit Suicidal Ideation via Longitudinal and Information Environment Signals on Social Mediacited by 3
  12. 2025Somatic in the East, Psychological in the West?: Investigating Clinically-Grounded Cross-Cultural Depression Symptom Expression in LLMscited by 2
8 more
  1. 2026Responsible Evaluation of AI for Mental Healthcited by 2
  2. 2025TWICE: Modeling the Temporal Evolution of Personalized User Behavior via Event-Driven Agentscited by 2
  3. 2025Explainable Multimodal Depression Recognition in Clinical Interviews via PHQ-Aligned Symptom Summarizationcited by 1
  4. 2025CNSocialDepress: A Chinese Social Media Dataset for Depression Risk Detection and Structured Analysiscited by 1
  5. 2026Learning Evidence of Depression Symptoms via Prompt Inductioncited by 1
  6. 2026SynSym: A Synthetic Data Generation Framework for Psychiatric Symptom Identificationcited by 0
  7. 2026SSR: Can Simulated Patients Learn to Stigmatize Themselves? Modeling Self-Stigma through Internal Monologuecited by 0
  8. 2026Self-Evolving Human-Centered Framework for Explainable Depression Symptom Annotationcited by 0