UMEval: a unified framework for explainable medical term semantic evaluation with large language models.
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| Title: | UMEval: a unified framework for explainable medical term semantic evaluation with large language models. |
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| Authors: | Liu S; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Feng L; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Luo Y; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Wang B; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Chen P; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Wang X; School of Medical Informatics and Engineering, Zunyi Medical University, Zunyi, 563000 China., Xu H; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Ma D; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Chen M; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Chen C; School of Data Science and Engineering, East China Normal University, Shanghai, 200062 China., Li H; State Key Laboratory of Public Big Data, College of Computer Science and Technology, Guizhou University, Guiyang, 550025 China., Wang Y; School of Data Science and Engineering, East China Normal University, Shanghai, 200062 China. |
| Source: | Health information science and systems [Health Inf Sci Syst] 2026 Apr 07; Vol. 14 (1), pp. 52. Date of Electronic Publication: 2026 Apr 07 (Print Publication: 2026). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Country of Publication: England NLM ID: 101638060 Publication Model: eCollection Cited Medium: Print ISSN: 2047-2501 (Print) Linking ISSN: 20472501 NLM ISO Abbreviation: Health Inf Sci Syst Subsets: PubMed not MEDLINE |
| Database: | MEDLINE Ultimate |
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