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

Infodemiology and Infoveillance (1560) Medicine 2.0: Social Media, Open, Participatory, Collaborative Medicine (1914) Ontologies, Classifications, and Coding (324) Infoveillance, Infodemiology, Digital Disease Surveillance, Infodemic Management (1139) Chatbots and Conversational Agents (741) Generative Language Models Including ChatGPT (709) Public (e)Health, Digital Epidemiology and Public Health Informatics (1011) Outbreak and Pandemic Preparedness and Management (1826)

Published on in Vol 26 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/49139, first published .
Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study

Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study

Use of Large Language Models to Assess the Likelihood of Epidemics From the Content of Tweets: Infodemiology Study

Authors of this article:

Michael S Deiner1, 2 Author Orcid Image ;   Natalie A Deiner3 Author Orcid Image ;   Vagelis Hristidis4 Author Orcid Image ;   Stephen D McLeod1, 2, 5 Author Orcid Image ;   Thuy Doan1, 2, 6 Author Orcid Image ;   Thomas M Lietman1, 2, 6 Author Orcid Image ;   Travis C Porco1, 2, 6 Author Orcid Image
Article Authors Cited by (12) Tweetations (7) Metrics

Journals

  1. Deiner M, Honcharov V, Li J, Mackey T, Porco T, Sarkar U. Large Language Models Can Enable Inductive Thematic Analysis of a Social Media Corpus in a Single Prompt: Human Validation Study. JMIR Infodemiology 2024;4:e59641 View
  2. Branda F. Harnessing computational tools of the digital era for enhanced infection control. BMC Medical Informatics and Decision Making 2024;24(1) View
  3. Kang L, Hu J, Cai K, Jing W, Liu M, Liang W. The Intelligent Infectious Disease Active Surveillance and early warning system in China: An application of dengue prevention and control. Global Transitions 2024;6:249 View
  4. Lu Y, Aleta A, Du C, Shi L, Moreno Y. LLMs and generative agent-based models for complex systems research. Physics of Life Reviews 2024;51:283 View
  5. Salaris S, Ocagli H, Casamento A, Lanera C, Gregori D. Foodborne Event Detection Based on Social Media Mining: A Systematic Review. Foods 2025;14(2):239 View
  6. Zhang J, Zhou J, Zhou L, Ba Z. Extracting Multifaceted Characteristics of Patients With Chronic Disease Comorbidity: Framework Development Using Large Language Models. JMIR Medical Informatics 2025;13:e70096 View
  7. Qiang S, Zhang H, Liao Y, Zhang Y, Gu Y, Wang Y, Xu Z, Shi H, Han N, Yu H. Application of Large Language Models in Stroke Rehabilitation Health Education: 2-Phase Study. Journal of Medical Internet Research 2025;27:e73226 View
  8. Soltani M, Dara R, Poljak Z, Dubé C, Bruce N, Sharif S. Leveraging social media and google trends to identify waves of avian influenza outbreaks in USA and Canada. Expert Systems with Applications 2025;291:128482 View
  9. Deiner M, Deiner R, Fathy C, Deiner N, Hristidis V, McLeod S, Bukowski T, Doan T, Seitzman G, Lietman T, Porco T. Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study. Journal of Medical Internet Research 2025;27:e65226 View
  10. Kaur J, Butt Z. AI-driven epidemic intelligence: the future of outbreak detection and response. Frontiers in Artificial Intelligence 2025;8 View

Books/Policy Documents

  1. Musunuri R, Bhatt A. Improving Healthcare Quality and Patient Engagement. View

Conference Proceedings

  1. Nguyen Q, Nguyen H, Tang Q, Truong T, Pham V, Le L, Williams-King D. Proceedings of the 2025 Symposium on Eye Tracking Research and Applications. Learning Disorder Detection Using Eye Tracking: Are Large Language Models Better Than Machine Learning? View