DietNerd: A Nutrition Question-Answering System That Summarizes and Evaluates Peer-Reviewed Scientific Articles
DietNerd is a large language model-based system designed to enhance public health education in diet and nutrition. The system responds to user questions with concise, evidence-based summaries and assesses the quality and potential biases of cited research. This paper describes the system’s workflow, back-end implementation, and the prompts used. Accuracy and quality-of-response results are presented based on an automated comparison against systematic surveys and against the responses of similar state-of-the-art systems through human feedback from registered dietitians. DietNerd is among the highest-evaluated of these systems and is unique in combining safety features with sophisticated source analysis. Thus, DietNerd could be a tool to bridge the gap between complex scientific literature and public understanding.
Authors
- Shela Wu
- Dennis E. Shasha (ORCID: https://orcid.org/0000-0002-7036-3312)
- Zubair Yacub
Institutions
- University of Illinois Urbana-Champaign (US)
- Courant Institute of Mathematical Sciences (US)
- New York University (US)
Publication Details
- Journal
- Applied Sciences
- Published
- 2024-10-06
- DOI
- https://doi.org/10.3390/app14199021
- Citations
- 3
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 1.04