Fast, Accurate Assignment of Clinical Diagnoses From Patient Notes by a Large Language Model: Critical Pediatric Pneumonia as a Use Case
The GPT-4o LLM was able to accurately and rapidly identify critically ill children with vs. without bacterial pneumonia. This study suggests similar tools could be developed to automate and accelerate processes typically requiring manual chart review.
Authors
- Sara J. Deakyne Davies (ORCID: https://orcid.org/0000-0002-8602-1624)
- Seth Russell (ORCID: https://orcid.org/0000-0002-2436-1367)
- Marisa Payan
- Peter E. DeWitt (ORCID: https://orcid.org/0000-0002-6391-0795)
- Blake Martin (ORCID: https://orcid.org/0000-0001-5683-8310)
- Jaime LaVelle
- James Leonard Mitchell (ORCID: https://orcid.org/0000-0001-6051-2567)
- Tellen D. Bennett (ORCID: https://orcid.org/0000-0003-1483-4236)
Institutions
- Children's Hospital Colorado (US)
- University of Colorado Denver (US)
Publication Details
- Journal
- Critical Care Explorations
- Published
- 2025-11-24
- DOI
- https://doi.org/10.1097/cce.0000000000001350
- Primary Topic
- Clinical Reasoning and Diagnostic Skills
- Type
- article
- Field-Weighted Citation Impact
- 0.00