Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology
Journal:
arXiv
Published Date:
Jul 10, 2025
Abstract
Large language models (LLMs) show promise for supporting clinical
decision-making in complex fields such as rheumatology. Our evaluation shows
that smaller language models (SLMs), combined with retrieval-augmented
generation (RAG), achieve higher diagnostic and therapeutic performance than
larger models, while requiring substantially less energy and enabling
cost-efficient, local deployment. These features are attractive for
resource-limited healthcare. However, expert oversight remains essential, as no
model consistently reached specialist-level accuracy in rheumatology.
