Extracting antibiotic susceptibility from free-text microbiology reports using natural language processing.

Journal: Infection control and hospital epidemiology
Published Date: Jul 31, 2025

Abstract

There is a clinical need to appropriately apply large language model (LLM)-based systems for use in infectious diseases. We sought to use LLM and machine learning for extracting antibiotic susceptibility from clinical microbiology free-text reports, allowing use for outbreak detection, increasing information gathering efficiency, and public health reporting.

Authors

  • Andrew Chou
    Pain Research, Informatics, Multi-morbidities, and Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, Connecticut, USA.
  • Ronald George Hauser
    VA Connecticut Healthcare System, West Haven, CT, USA.
  • Lori A Bastian
    VA Connecticut Healthcare System, West Haven, CT, USA.
  • Cynthia A Brandt
    Yale School of Medicine, New Haven, CT VA Connecticut Healthcare System, West Haven, CT.
  • Barbara W Trautner
    Center for Innovations in Quality Effectiveness, and Safety, Michael E. DeBakey Veterans Affairs Medical Center and Baylor College of Medicine, Houston, TX, USA.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals