This paper is in the following e-collection/theme issue:

Applications of AI (246) Ethical, Legal, and Social Issues in AI (91)

Published on in Vol 2 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41205, first published .
Enabling Early Health Care Intervention by Detecting Depression in Users of Web-Based Forums using Language Models: Longitudinal Analysis and Evaluation

Enabling Early Health Care Intervention by Detecting Depression in Users of Web-Based Forums using Language Models: Longitudinal Analysis and Evaluation

Enabling Early Health Care Intervention by Detecting Depression in Users of Web-Based Forums using Language Models: Longitudinal Analysis and Evaluation

Authors of this article:

David Owen1 Author Orcid Image ;   Dimosthenis Antypas1 Author Orcid Image ;   Athanasios Hassoulas2 Author Orcid Image ;   Antonio F Pardiñas3 Author Orcid Image ;   Luis Espinosa-Anke1 Author Orcid Image ;   Jose Camacho Collados1 Author Orcid Image
Article Authors Cited by (13) Tweetations (10) Metrics

Journals

  1. Owen D, Lynham A, Smart S, Pardiñas A, Camacho Collados J. AI for Analyzing Mental Health Disorders Among Social Media Users: Quarter-Century Narrative Review of Progress and Challenges. Journal of Medical Internet Research 2024;26:e59225 View
  2. Deng T, Urbaczewski A, Lee Y, Barman-Adhikari A, Dewri R. Identifying Marijuana Use Behaviors Among Youth Experiencing Homelessness Using a Machine Learning–Based Framework: Development and Evaluation Study. JMIR AI 2024;3:e53488 View
  3. Wang J, Xi R, Wang Y, Gao H, Gao M, Zhang X, Zhang L, Zhang Y. Toward molecular diagnosis of major depressive disorder by plasma peptides using a deep learning approach. Briefings in Bioinformatics 2024;26(1) View
  4. Dalal S, Jain S, Dave M. Review of Advancements in Depression Detection Using Social Media Data. IEEE Transactions on Computational Social Systems 2025;12(1):77 View
  5. Nejadshamsi S, Karami V, Ghourchian N, Armanfard N, Bergman H, Grad R, Wilchesky M, Khanassov V, Vedel I, Abbasgholizadeh Rahimi S. Development and Feasibility Study of HOPE Model for Prediction of Depression Among Older Adults Using Wi-Fi-based Motion Sensor Data: Machine Learning Study. JMIR Aging 2025;8:e67715 View
  6. Jin Y, Liu J, Li P, Wang B, Yan Y, Zhang H, Ni C, Wang J, Li Y, Bu Y, Wang Y. The Applications of Large Language Models in Mental Health: Scoping Review. Journal of Medical Internet Research 2025;27:e69284 View
  7. Alhazzaa L, Curcin V. Profiling Generalized Anxiety Disorder on Social Networks: Content and Behavior Analysis. Journal of Medical Internet Research 2025;27:e53399 View
  8. Ghouch B, Khreich W. Reducing false alarms by identifying depression-mimicking expressions. Neural Computing and Applications 2025 View

Books/Policy Documents

  1. Bucur A. Experimental IR Meets Multilinguality, Multimodality, and Interaction. View

Conference Proceedings

  1. Kimera R, Rim D, Kirabira J, Udomah U, Choi H. 2023 14th International Conference on Information and Communication Technology Convergence (ICTC). Enhanced Labeling Technique for Reddit Text and Fine-Tuned Longformer Models for Classifying Depression Severity in English and Luganda View
  2. Rajapakse T, Yates A, de Rijke M. Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region. Simple Transformers: Open-source for All View
  3. Hassan E, Bhatnagar R, El-Hafeez T, Shams M. 2025 7th International Conference on Signal Processing, Computing and Control (ISPCC). Detection of Suicide and Depression for Early Intervention and Initiative-taking Mental Healthcare View
  4. Ge Z, Hu N, Li D, Wang Y, Qi S, Xu Y, Shi H, Zhang J. 2025 IEEE 41st International Conference on Data Engineering Workshops (ICDEW). A Survey of Large Language Models in Mental Health Disorder Detection on Social Media View