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bioRxiv · 10.1101/2023.04.19.537463

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

Chen, Q.·Sun, H.·Liu, H.·Jiang, Y.·Ran, T.·Jin, X.·Xiao, X.·Lin, Z.·Niu, Z.·Chen, H.
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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.

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Chen, Q., Sun, H., Liu, H., Jiang, Y., Ran, T., Jin, X., Xiao, X., Lin, Z., Niu, Z., Chen, H.. 2023-04-20. A Comprehensive Benchmark Study on Biomedical Text Generation and Mining with ChatGPT. https://doi.org/10.1101/2023.04.19.537463

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