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

Generative Language Models Including ChatGPT (435) AI Language Models in Health Care (90) Instruments and Questionnaires for Nutrition and Food Intake (180) Information Retrieval (321) Information Seeking, Information Needs (516)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67677, first published .
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

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 Tweetations Metrics

Yu Hou   1 , PhD ;   Jeffrey R Bishop   2 , PharmD, MS ;   Hongfang Liu   3 , PhD ;   Rui Zhang   1, 4 , PhD

1 Division of Computational Health Sciences, University of Minnesota, Minneapolis, MN, United States

2 Department of Experimental and Clinical Pharmacology, University of Minnesota, Minneapolis, MN, United States

3 Department of Health Data Science and Artificial Intelligence, UTHealth, Houston, TX, United States

4 Center for Learning Health System Sciences, University of Minnesota, Minneapolis, MN, United States

Corresponding Author:

  • Rui Zhang, PhD
  • Division of Computational Health Sciences
  • University of Minnesota
  • 11-132 Phillips-Wangensteen Building
  • 516 Delaware Street SE
  • Minneapolis, MN, 55455
  • United States
  • Phone: 1 6126261999
  • Email: ruizhang@umn.edu