Building an intelligent diabetes Q&A system with knowledge graphs and large language models
This study demonstrates the effectiveness of integrating large language models with structured knowledge graphs to improve medical question-answering systems. The proposed approach offers a promising framework for advancing diabetes management and other healthcare applications, providing a solid foundation for future personalized healthcare interventions.
Authors
- Zhao Qin (ORCID: https://orcid.org/0000-0001-5696-8553)
- Cora Un In Wong (ORCID: https://orcid.org/0000-0001-5523-4355)
- Xiaolong Chen (ORCID: https://orcid.org/0000-0002-8704-8212)
- Hongfeng Zhang (ORCID: https://orcid.org/0000-0002-7586-2364)
- Dongze Wu (ORCID: https://orcid.org/0000-0002-5571-8728)
- Zhidong Zang (ORCID: https://orcid.org/0000-0002-4165-7178)
Institutions
- Southwest Jiaotong University (CN)
- Macao Polytechnic University (MO)
- Yangzhou University (CN)
Publication Details
- Journal
- Frontiers in Public Health
- Published
- 2025-02-20
- DOI
- https://doi.org/10.3389/fpubh.2025.1540946
- Citations
- 4
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 9.92
Funders
- National Social Science Fund of China