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Leveraging Large Language Models for Cancer Variant Classification: A Comparative Study of GPT-4o, LLaMA 3, and Qwen 2.5.

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Title: Leveraging Large Language Models for Cancer Variant Classification: A Comparative Study of GPT-4o, LLaMA 3, and Qwen 2.5.
Authors: Lin KH; Department of Information Management, Taipei Veterans General Hospital, Taipei, 11267, Taiwan, R.O.C.; Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, 11219, Taiwan, R.O.C., Chen PC; Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei, 11267, Taiwan, R.O.C.; School of Medicine, National Yang Ming Chiao Tung University, 112304, Taipei, Taiwan, R.O.C., Kuo CT; Department of Information Management, Taipei Veterans General Hospital, Taipei, 11267, Taiwan, R.O.C.; Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, 11219, Taiwan, R.O.C., Chu YC; Department of Information Management, Taipei Veterans General Hospital, Taipei, 11267, Taiwan, R.O.C.; Department of Information Management, National Taipei University of Nursing and Health Sciences, Taipei, 11219, Taiwan, R.O.C., Yeh YC; Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei, 11267, Taiwan, R.O.C.; School of Medicine, National Yang Ming Chiao Tung University, 112304, Taipei, Taiwan, R.O.C.
Source: Studies in health technology and informatics [Stud Health Technol Inform] 2025 Aug 07; Vol. 329, pp. 1728-1729.
Publication Type: Journal Article; Comparative Study
Journal Info: Publisher: IOS Press Country of Publication: Netherlands NLM ID: 9214582 Publication Model: Print Cited Medium: Internet ISSN: 1879-8365 (Electronic) Linking ISSN: 09269630 NLM ISO Abbreviation: Stud Health Technol Inform Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1879-8365
DOI:10.3233/SHTI251185