Accessibility settings

This paper is in the following e-collection/theme issue:

Generative Language Models Including ChatGPT (900) Information Retrieval (368) Information Seeking, Information Needs (602) Instruments and Questionnaires for Nutrition and Food Intake (234) AI Language Models in Health Care (298)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67677, first published .
Person's hands holding pills poured from a white bottle, blue background

Improving Dietary Supplement Information Retrieval: Development of a Retrieval-Augmented Generation System With Large Language Models

Improving Dietary Supplement Information Retrieval: Development of a Retrieval-Augmented Generation System With Large Language Models

Authors of this article:

Yu Hou1 Author Orcid Image ;   Jeffrey R Bishop2 Author Orcid Image ;   Hongfang Liu3 Author Orcid Image ;   Rui Zhang1, 4 Author Orcid Image
Article Authors Cited by (12) Tweetations Metrics

Journals

  1. Zuo J, Niu J. Construction of Journal Knowledge Graph Based on Deep Learning and LLM. Electronics 2025;14(9):1728 View
  2. Belkhouribchia J, Pen J. Large language models in clinical nutrition: an overview of its applications, capabilities, limitations, and potential future prospects. Frontiers in Nutrition 2025;12 View
  3. Anghelescu A, Munteanu C, Anghelescu L, Onose G. ”A Midsummer Night’s Dream” quest for truth: From ChatGPT “hallucinations” to RAG reasoning and ACURAI precision — a scoping review on detection, minimizing, and (almost) complete error elimination and enhancing Large Language Models' re-liability. Balneo and PRM Research Journal 2025;16(Vol 16 No. 3):847 View
  4. Xu C, Yu Y, Khadakkar G, Xie J, Xu D, Yao Q. Multimodal knowledge expansion widget powered by plant protein phosphorylation database and ChatGPT. Frontiers in Bioinformatics 2025;5 View
  5. Miao Y, Zhao Y, Luo Y, Wang H, Wu Y. Improving Large Language Model Applications in the Medical and Nursing Domains With Retrieval-Augmented Generation: Scoping Review. Journal of Medical Internet Research 2025;27:e80557 View
  6. Wang S, Zhang Y, Gao Y, He X, Deng G, Du J. Knowledge graph-augmented large language models for reconstructing life course risk pathways: a gestational diabetes mellitus-to-dementia case study. Journal of the American Medical Informatics Association 2026;33(3):632 View
  7. Wang Y, Luan Y, Cheng S, Hao M, Tan W, Hu R, Yao Z, Wang J, Wu J. A multi-layer retrieval-augmented large language model framework for enhancing hypertension education. Hypertension Research 2026;49(4):1428 View
  8. An H, Dong Q, Doulgeraki A, Nychas G, Zhou Z, Liu Y. Knowledge graph and large language model synergy for food safety: Approaches and perspectives. Trends in Food Science & Technology 2026;170:105592 View
  9. Hou Y, Gubili J, Jain P, Lam C, Chatterjee A, Mao J. Evaluation of a RAG-Based LLM for Evidence-Based Herb and Supplement Information in Cancer Care (Preprint). JMIR Cancer 2025 View
  10. Zong H, Cha J, Wang J, Song Y, Zhao Y, Shi M, Shen B. A Dataset for Evaluating Large Language Models on Chinese National Medical Licensing Examinations. Scientific Data 2026 View

Conference Proceedings

  1. R R, Mishra M, G S, B S, P L, N V K. 2025 5th International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN). Retrieval-Augmented Graph Neural Model for Medical Question Answering System View
  2. Jayaraman P, Partheeban P, Nagarajan K, Koushik N, Manikandan G, Alwin J. 2026 International Conference on Data Science, Agents and Artificial Intelligence (ICDSAAI). Smart Retrieval of Industrial Standards with LLM and Elastic search View