A Comprehensive Benchmark Study on Biomedical Text Generation and Mining with ChatGPT

Qijie Chen, Haotong Sun,Haoyang Liu, Yinghui Jiang,Ting Ran,Xurui Jin, Xianglu Xiao, Zhimin Lin,Zhangming Niu, Hongming Chen

biorxiv(2023)

引用 5|浏览30
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摘要
In recent years, the development of natural language process (NLP) technologies and deep learning hardware has led to significant improvement in large language models(LLMs). The ChatGPT, the state-of-the-art LLM built on GPT-3.5, shows excellent capabilities in general language understanding and reasoning. Researchers also tested the GPTs on a variety of NLP related tasks and benchmarks and got excellent results. To evaluate the performance of ChatGPT on biomedical related tasks, this paper presents a comprehensive benchmark study on the use of ChatGPT for biomedical corpus, including article abstracts, clinical trials description, biomedical questions and so on. Through a series of experiments, we demonstrated the effectiveness and versatility of Chat-GPT in biomedical text understanding, reasoning and generation. ### Competing Interest Statement The authors have declared no competing interest.
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