Qwen-2.5 Outperforms Other Large Language Models in the Chinese National Nursing Licensing Examination: Retrospective Cross-Sectional Comparative Study
This study is the first to evaluate the performance of 7 LLMs on the CNNLE and that the integration of models via machine learning significantly boosted accuracy, reaching 90.8%. These findings demonstrate the transformative potential of LLMs in revolutionizing health care education and call for further research to refine their capabilities and expand their impact on examination preparation and professional training.
Authors
- Fang Zhang
- Wanqin Hu (ORCID: https://orcid.org/0000-0003-2548-5801)
- Jiani Yan (ORCID: https://orcid.org/0009-0007-5373-0305)
- Shiben Zhu (ORCID: https://orcid.org/0000-0002-0846-0453)
- Yang Zhi (ORCID: https://orcid.org/0009-0007-7354-5879)
Institutions
- City University of Hong Kong (HK)
- Nanfang Hospital (CN)
- Shenzhen Bao'an District People's Hospital (CN)
- Metropolitan University (BD)
- Shenzhen Children's Hospital (CN)
- Southern Medical University (CN)
Publication Details
- Journal
- JMIR Medical Informatics
- Published
- 2024-12-20
- DOI
- https://doi.org/10.2196/63731
- Citations
- 19
- Primary Topic
- Nursing Diagnosis and Documentation
- Type
- article
- Field-Weighted Citation Impact
- 27.67