Benchmarking large language models GPT-4o, llama 3.1, and qwen 2.5 for cancer genetic variant classification
Abstract Classifying cancer genetic variants based on clinical actionability is crucial yet challenging in precision oncology. Large language models (LLMs) offer potential solutions, but their performance remains underexplored. This study evaluates GPT-4o, Llama 3.1, and Qwen 2.5 in classifying gene...
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| Main Authors: | Kuan-Hsun Lin, Tzu-Hang Kao, Lei-Chi Wang, Chen-Tsung Kuo, Paul Chih-Hsueh Chen, Yuan-Chia Chu, Yi-Chen Yeh |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | npj Precision Oncology |
| Online Access: | https://doi.org/10.1038/s41698-025-00935-4 |
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