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

Artificial Intelligence (5152) Infodemic Management (80) Misinformation and Disinformation Outbreaks and Information Prevalence Studies (184) Bots and AI Approaches to Detect and Counter Misinformation (30) Research Methodology - AI (219) Applications of AI (1152)

Published on in Vol 28 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/75500, first published .
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Intervention in Health Misinformation Using Large Language Models for Automated Detection, Thematic Analysis, and Inoculation: Case Study on COVID-19

Intervention in Health Misinformation Using Large Language Models for Automated Detection, Thematic Analysis, and Inoculation: Case Study on COVID-19

Authors of this article:

Samira Malek1 Author Orcid Image ;   Christopher Griffin2, 3 Author Orcid Image ;   Robert D Fraleigh2 Author Orcid Image ;   Robert Lennon4 Author Orcid Image ;   Vishal Monga5 Author Orcid Image ;   Lijiang Shen6 Author Orcid Image
Article Authors Cited by (7) Tweetations (28) Metrics

Journals

  1. Vijayakumar K, Parthasarathy P, Ponni Valavan M, Anandaram H, Susheelkumar Sreedharan P, Sahadevan J. Enhanced label-free SARS-CoV-2 biomarker detection using a gold-functionalized Ag–ZnO–Fe₂O₃ multilayer surface plasmon resonance biosensor. Optik 2026;352:172839 View
  2. Hu Y. AI-enabled health communication to address misinformation on social media: a mini review. Frontiers in Communication 2026;11 View
  3. Shahzad K, Javeed A, Ahmad S, Latif M, Saleem K. Big data analytics and sentiment analysis for health misinformation detection: a systematic literature review of influencing factors, implementation challenges and a data-driven adoption framework. Frontiers in Big Data 2026;9 View
  4. Rajan M. AI conversational agents as population health infrastructure: promise, peril, and the case for public-interest design. Frontiers in Public Health 2026;14 View
  5. Baydili İ, Tasci B, Dogan S, Tuncer T. Generative AI, Health Misinformation, and Medical Deepfakes: Implications for Diagnostic Safety and Clinical Practice—A Narrative Review. Diagnostics 2026;16(21):3572 View
  6. Preetasha N, Mohammed N, Ahmed S, Elahi M, Momen S. A unified framework for sentiment classification and topic modeling of mHealth app reviews. DIGITAL HEALTH 2026;12 View

Conference Proceedings

  1. Ljubi I, Vukovic M. 2026 11th International Conference on Smart and Sustainable Technologies (SpliTech). Domain-Adaptive Pretraining for Healthcare-Related Croatian Twitter Classification View