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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/65226, first published .
Robot and public health official analyze COVID-19 data on large screen

Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study

Use of Large Language Models to Classify Epidemiological Characteristics in Synthetic and Real-World Social Media Posts About Conjunctivitis Outbreaks: Infodemiology Study

Journals

  1. Kaur J, Butt Z. AI-driven epidemic intelligence: the future of outbreak detection and response. Frontiers in Artificial Intelligence 2025;8 View
  2. Chen P, Gu H, Lo H, Chang W, Lai C, Lai S, Cheng A, Ng P. Leveraging Large Language Models for Early Detection of Anomaly Work Injury Cases: Data-Driven Approach to Rehabilitation Efficiency. JMIR Rehabilitation and Assistive Technologies 2026;13:e80607 View
  3. Jiang S, Ren H, Gao Y, Zhang Y, Qi L, Xiao D, Fan J, Tang R, Wang W. Large language models for spreading dynamics in complex systems. Physics Reports 2026;1171:1 View
  4. Li Q, Cheng Z, Cao F, Wang X, Bachani A. Evaluating large language models for selected public health research and practice tasks: A 100-question benchmark of reliability, workflow-assisted recoverability, and correct source-grounded abstention. DIGITAL HEALTH 2026;12 View

Books/Policy Documents

  1. . Epidemic Modeling. View
  2. Lazebnik T. Epidemic Modeling. View

Conference Proceedings

  1. Zhao C, Yang H. Proceedings of the 2026 2nd International Conference on Big Data and Intelligent Medicine. Evaluating LLM Robustness Under Domain-Specific Prompt Perturbations in Public Health Applications View