Published on in Vol 13 (2025)

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Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/75279, first published .
Leveraging Retrieval-Augmented Large Language Models for Dietary Recommendations With Traditional Chinese Medicine’s Medicine Food Homology: Algorithm Development and Validation

Leveraging Retrieval-Augmented Large Language Models for Dietary Recommendations With Traditional Chinese Medicine’s Medicine Food Homology: Algorithm Development and Validation

Leveraging Retrieval-Augmented Large Language Models for Dietary Recommendations With Traditional Chinese Medicine’s Medicine Food Homology: Algorithm Development and Validation

Hangyu Sha   1, 2 * , BEng ;   Fan Gong   3 * , PhD ;   Bo Liu   4 * , PhD ;   Runfeng Liu   1, 2 , BEng ;   Haofen Wang   5 , PhD ;   Tianxing Wu   1, 2 , PhD

1 School of Computer Science and Engineering, Southeast University, Nanjing, China

2 Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications (Southeast University), Ministry of Education, China

3 Department of Endocrinology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, China

4 Informatization Office, Shanghai University of Traditional Chinese Medicine, Shanghai, China

5 College of Design and Innovation, Tongji University, Shanghai, China

*these authors contributed equally

Corresponding Author:

  • Tianxing Wu, PhD
  • School of Computer Science and Engineering
  • Southeast University
  • 2 Southeast University Road, Jiangning District
  • Nanjing 210096
  • China
  • Phone: 86 15077889931
  • Email: tianxingwu@seu.edu.cn