Evaluation of LLMs accuracy and consistency in the registered dietitian exam through prompt engineering and knowledge retrieval.

Iman Azimi¹, Mohan Qi², Li Wang³, Amir M Rahmani⁴, Youlin Li²

¹Department of Engineering, iHealth Labs, Sunnyvale, CA, 94085, United States. iman.azimi@ihealthlabs.com.

²Department of Engineering, iHealth Labs, Sunnyvale, CA, 94085, United States.

³Department of Clinical Research, iHealth Labs, Sunnyvale, CA, 94085, United States.

⁴School of Nursing and Department of Computer Science, University of California Irvine, Irvine, CA, 92697, United States.

PubMed PMC DOI PDF

Abstract

Large language models (LLMs) are fundamentally transforming human-facing applications in the health and well-being domains: boosting patient engagement, accelerating clinical decision-making, and facilitating medical education. Although state-of-the-art LLMs have shown superior performance in several conversational applications, evaluations within nutrition and diet applications are still insuffic…

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