Development and Performance of a Large Language Model for the Quality Evaluation of Multi‐Language Medical Imaging Guidelines and Consensus
The QPC-HASE-GuidelineEval algorithm, powered by LLMs, showed strong potential for improving the efficiency, scalability, and multi-language capability of guideline evaluations, though further enhancements are needed to handle more complex tasks that require deeper interpretation.
Authors
- Han Lv (ORCID: https://orcid.org/0000-0001-9559-4777)
- Jing Sun (ORCID: https://orcid.org/0000-0002-0097-2438)
- Yaolong Chen (ORCID: https://orcid.org/0000-0002-9841-5233)
- Xufei Luo (ORCID: https://orcid.org/0000-0003-0811-6326)
- Zhenchang Wang (ORCID: https://orcid.org/0000-0001-8190-6469)
- Wenjun He (ORCID: https://orcid.org/0000-0002-6993-1837)
- Zhixiang Wang (ORCID: https://orcid.org/0000-0002-9091-2673)
- Zhenhua Yang (ORCID: https://orcid.org/0000-0002-7086-0300)
- Hui Liu (ORCID: https://orcid.org/0000-0001-8245-6025)
- Jia Li (ORCID: https://orcid.org/0000-0003-3152-3253)
Institutions
- Hong Kong Baptist University (HK)
- Capital Medical University (CN)
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- Beijing Friendship Hospital (CN)
- Southern Medical University (CN)
- Lanzhou University (CN)
Publication Details
- Journal
- Journal of Evidence-Based Medicine
- Published
- 2025-04-03
- DOI
- https://doi.org/10.1111/jebm.70020
- Citations
- 1
- Primary Topic
- Clinical practice guidelines implementation
- Type
- article
- Field-Weighted Citation Impact
- 1.88
Funders
- Capital Medical University
- Natural Science Foundation of Beijing Municipality
- National Key Research and Development Program of China