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

Reviews (133) Depression and Mood Disorders; Suicide Prevention (1687) Psychiatry (94) Natural Language Processing (917) Clinical Mental Health Informatics (68) Machine Learning (2074)

Published on in Vol 13 (2024)

This is a member publication of University of Toronto

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55067, first published .
Screening for Depression Using Natural Language Processing: Literature Review

Screening for Depression Using Natural Language Processing: Literature Review

Screening for Depression Using Natural Language Processing: Literature Review

Authors of this article:

Bazen Gashaw Teferra1 Author Orcid Image ;   Alice Rueda1 Author Orcid Image ;   Hilary Pang1 Author Orcid Image ;   Richard Valenzano2 Author Orcid Image ;   Reza Samavi3 Author Orcid Image ;   Sridhar Krishnan3 Author Orcid Image ;   Venkat Bhat1, 4 Author Orcid Image
Article Authors Cited by (11) Tweetations Metrics

Journals

  1. Alasmari A. A Scoping Review of Arabic Natural Language Processing for Mental Health. Healthcare 2025;13(9):963 View
  2. Luo X, Li Y, Xu J, Zheng Z, Ying F, Huang G. AI in Medical Questionnaires: Scoping Review. Journal of Medical Internet Research 2025;27:e72398 View
  3. Rahman A, Khan M, Bishnu K, Rozario U, Ishraq A, Mridha M, Aung Z. Multilingual sentiment analysis in restaurant reviews using aspect focused learning. Scientific Reports 2025;15(1) View
  4. Lim D, Lee K, Jo J, Lim H, Bae H, Kang C. Web-Based Platform for Quantitative Depression Risk Prediction via VAD Regression on Korean Text and Multi-Anchor Distance Scoring. Applied Sciences 2025;15(18):10170 View
  5. Ren W, Xue X, Liu L, Huang J. AI Applications in Depression Detection and Diagnosis: Bibliometric and Visual Analysis of Trends and Future Directions. JMIR Mental Health 2025;12:e79293 View
  6. Weber S, Deperrois N, Heun R, Frühschütz L, Monn A, Homan S, Häfliger A, Seifritz E, Kowatsch T, Jäger L, Schultebraucks K, Gershov S, Mocellin J, Kleim B, Olbrich S. Using a fine-tuned large language model for symptom-based depression evaluation. npj Digital Medicine 2025;8(1) View
  7. Wijayanti E, Abror A, Rachmawati U, Agustina C, Umniyati H, Munti D, Rahmat E, Diansyah A. MOODMIND: Artificial Intelligence for Major Depressive Disorder Screening in Tuberculosis Patients. F1000Research 2025;14:1079 View
  8. Amit Phadikar , Himadri Mandal . Depression Detection by Facial Emotion Recognition Using Deep Neural Network. International Journal of Latest Technology in Engineering Management & Applied Science 2025;14(10):364 View

Books/Policy Documents

  1. Narwaria M, Mishra R, Jaiswal S, Dwivedi V, Upadhyay P, Yadav S. Demystifying the Role of Natural Language Processing (NLP) in Mental Health. View

Conference Proceedings

  1. U R, P N, J R, A Y, G S, M J. 2025 International Conference on Electronics and Renewable Systems (ICEARS). Empirical Evaluation of Social Networking Data to Classify Depressed Users based on Hybrid Deep Learning Stagey View
  2. Joy S, Krishna B, Rajesh S, P S N. 2025 International Conference on Intelligent Communication Networks and Computational Techniques (ICICNCT). Deep Learning for Mental Health: Attention-Driven Multilayer CNN for Audio Depression Detection View