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

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

来源:bioRxiv_logobioRxiv
英文摘要

Abstract 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.

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

MindRank AI Ltd.MindRank AI Ltd.Guangzhou LaboratoryMindRank AI Ltd.MindRank AI Ltd.MindRank AI Ltd.MindRank AI Ltd.Guangzhou Laboratory||College of Life Sciences, Nankai UniversityGuangzhou LaboratoryMindRank AI Ltd.

10.1101/2023.04.19.537463

医学研究方法生物科学研究方法、生物科学研究技术语言学

Jin Xurui,Lin Zhimin,Chen Hongming,Chen Qijie,Sun Haotong,Xiao Xianglu,Jiang Yinghui,Liu Haoyang,Ran Ting,Niu Zhangming.A Comprehensive Benchmark Study on Biomedical Text Generation and Mining with ChatGPT[EB/OL].(2025-03-28)[2025-06-08].https://www.biorxiv.org/content/10.1101/2023.04.19.537463.点此复制

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