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Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63190, first published .
Leveraging Large Language Models for Infectious Disease Surveillance—Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis

Leveraging Large Language Models for Infectious Disease Surveillance—Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis

Leveraging Large Language Models for Infectious Disease Surveillance—Using a Web Service for Monitoring COVID-19 Patterns From Self-Reporting Tweets: Content Analysis

Journals

  1. Melchane S, Elmir Y, Kacimi F, Boubchir L. A decision support approach to infectious disease classification using tweets and routine blood tests. Network Modeling Analysis in Health Informatics and Bioinformatics 2025;14(1) View
  2. Fieldhouse J, Ge J, Randhawa N, Wolking D, Genovese B, Mazet J, Desai A. The intersection of artificial intelligence with qualitative or mixed methods for communicable disease research: a scoping review. Public Health 2025;248:105961 View
  3. Li J, Tseng Y, Chen S, Chen K. Artificial intelligence in infection surveillance: Data integration, applications and future directions. Biomedical Journal 2026;49(2):100929 View
  4. Yang L, Shan L, Cao X, Cui J, Tong M, Niu Y, Zhang T. AI Agents and Epidemic Intelligence on Respiratory Infectious Diseases: Toward a Conceptual Framework Integrating Decision Support. Journal of Medical Internet Research 2026;28:e86936 View