Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology
Sabine Felde, Rüdiger Buchkremer, Gamal Chehab, Christian Thielscher, Jörg HW Distler +2 more
7/10/2025
cs.CLcs.AI
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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.
