Performance of a large language model for identifying central line-associated bloodstream infections (CLABSI) using real clinical notes

2024/10/30 by Guillermo Rodriguez‐Nava, Goar Egoryan, Katherine E Goodman +2 · 1 voice · 6 citations
Health Professions · Medicine · #Artificial Intelligence in Healthcare and Education #COVID-19 diagnosis using AI #Electronic Health Records Systems

paper · pdf · doi:10.1017/ice.2024.164

openalex publication_date 2024/10/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01

Abstract

We evaluated one of the first secure large language models approved for protected health information, for identifying central line-associated bloodstream infections (CLABSIs) using real clinical notes. Despite no pretraining, the model demonstrated rapid assessment and high sensitivity for CLABSI identification. Performance would improve with access to more patient data.

Citations

• Performance of ChatGPT on USMLE: Potential for AI-assisted medical education using large language models
• A Comprehensive Overview of Large Language Models

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Discussions

• New in ICHE from @grod11.bsky.social, @jlsalinas.bsky.social ▶️ Authors analyzed performance of a secure LLM approved for PHI in identifying CLABSI from clinical notes ▶️ Without pre-training, it d [bsky, 5 points, 1 comments]

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