Nursing Retrieval-Augmented Generation: Retrieval augmented generation for nursing question answering with large language models
The NurRAG system integrates domain-specific retrieval with LLMs generation to provide accurate, reliable, and traceable evidence-based nursing answers. The findings demonstrate the system's feasibility and potential to improve the accuracy of clinical knowledge access, support evidence-based nursing decision-making, and promote the safe application of artificial intelligence in nursing practice.
Authors
- Weixiang Luo (ORCID: https://orcid.org/0000-0003-3896-1854)
- Ronghui Liu
- Liping Xiong (ORCID: https://orcid.org/0000-0001-7924-8655)
- Qiqiao Zeng
Institutions
- Southern University of Science and Technology (CN)
- Southern Medical University Shenzhen Hospital (CN)
- Shenzhen Second People's Hospital (CN)
- South China University of Technology (CN)
Publication Details
- Journal
- International Journal of Nursing Sciences
- Published
- 2025-10-19
- DOI
- https://doi.org/10.1016/j.ijnss.2025.10.005
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00