Optimization of hepatological clinical guidelines interpretation by large language models: a retrieval augmented generation-based framework

Simone Kresevic, Mauro Giuffrè, Miloš Ajčević et al.

2024 · npj Digital Medicine · 177 citations

Large language models (LLMs) can potentially transform healthcare, particularly in providing the right information to the right provider at the right time in the hospital workflow. This study investigates the integration of LLMs into healthcare, specifically focusing on improving clinical decision support systems (CDSSs) through accurate interpretation of medical guidelines for chronic Hepatitis C Virus infection management. Utilizing OpenAI's GPT-4 Turbo model, we developed a customized LLM framework that incorporates retrieval augmented generation (RAG) and prompt engineering. Our framework…

Read the paper →

Explore this paper's citation graph on Constellation.