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

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

Books/Policy Documents

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