Accessibility settings

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

Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2355) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1998) Infodemiology and Infoveillance (1616) Natural Language Processing (994) Depression and Mood Disorders; Suicide Prevention (1798) Machine Learning (2306) Artificial Intelligence (2453) Outbreak and Pandemic Preparedness and Management (1856)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65434, first published .
Man stressed, looking at phone screen with notifications, at computer desk

Explainable Predictive Model for Suicidal Ideation During COVID-19: Social Media Discourse Study

Explainable Predictive Model for Suicidal Ideation During COVID-19: Social Media Discourse Study

Authors of this article:

Salah Bouktif1 Author Orcid Image ;   Akib Mohi Ud Din Khanday1 Author Orcid Image ;   Ali Ouni2 Author Orcid Image
Article Authors Cited by (12) Tweetations (1) Metrics

Journals

  1. Thaibah H, Banji O, Banji D, Almansour H, Alshammari T. Suicidality Risks Associated with Finasteride, a 5-Alpha Reductase Inhibitor: An Evaluation of Real-World Data from the FDA Adverse Event Reports. Pharmaceuticals 2025;18(7):957 View
  2. Li H, Liu Z, Zhang Z, Ping L, Gu W, Yao Y. Public Medical Appeals and Government Online Responses: Big Data Analysis Based on Chinese Digital Governance Platforms. Journal of Medical Internet Research 2025;27:e70087 View
  3. Espino Carrasco D, Palomino Alcántara M, Arbulú Pérez Vargas C, Santa Cruz Espino B, Dávila Valdera L, Vargas Cabrera C, Espino Carrasco M, Dávila Valdera A, Agurto Córdova L. Sustainability of AI-Assisted Mental Health Intervention: A Review of the Literature from 2020–2025. International Journal of Environmental Research and Public Health 2025;22(9):1382 View
  4. Hu Y, Wu R, Su M, Lin I, Shen C. Multimodal Multitask Learning for Predicting Depression Severity and Suicide Risk Using Pretrained Audio and Text Embeddings: Methodology Development and Application. JMIR Medical Informatics 2025;13:e66907 View
  5. Trentarossi B, Romão M, Barello S, Baptista M, Visonà S, Belli G. Digital Detection of Suicidal Ideation: A Scoping Review to Inform Prevention and Psychological Well-Being. Behavioral Sciences 2025;15(12):1601 View
  6. Bouktif S, Khanday A, Ouni A. Revealing the impact of COVID-19 on mental health through machine learning. JAMIA Open 2026;9(1) View
  7. Lokadjaja M, Kho J, Schulz P, Goh W. Large Language Models and Their Applications in Mental Health: Scoping Review. JMIR Mental Health 2026;13:e88057 View
  8. Mokheleli T, Makaba T, Ndayizigamiye P, Ndlovu N, Twinomurinzi H. Artificial intelligence in suicide risk assessment: a systematic literature review. Discover Artificial Intelligence 2026;6(1) View
  9. Kaur S. ARTIFICIAL INTELLIGENCE FOR EARLY DETECTION OF MENTAL HEALTH DISORDERS USING SOCIAL MEDIA DATA. International Journal of Engineering Technologies and Management Research 2026;13(4):47 View
  10. Kboubi F, Habacha Chaibi A. Hybrid transformer-based approaches for suicidal posts detection. International Journal of Computers and Applications 2026:1 View

Conference Proceedings

  1. Bai K, Radhika Y. 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG). Guardian Glance: An AI Powered Browser Extension for Proactive Mental Health Intervention and Suicide Prevention View
  2. Ramazanova A, Zhukabayeva T, Meraliyev B, Sadyk U. 2026 18th International Conference on Electronics, Computer, and Computation (ICECCO). Development of Multimodal Neural Network for Suicidal Ideation Detection Using Kazakh-Russian BERT and Attention Mechanism View