Wang Zhiping Paul, Bhandary Priyanka, Wang Yizhou, Moore Jason H
Department of Computational Biomedicine, Cedars Sinai Medical Center, 700 N. San Vicente Blvd, Pacific Design Center, Suite G-541, West Hollywood, CA, 90069, USA.
BioData Min. 2024 Jun 18;17(1):16. doi: 10.1186/s13040-024-00371-3.
GPT-4, as the most advanced version of OpenAI's large language models, has attracted widespread attention, rapidly becoming an indispensable AI tool across various areas. This includes its exploration by scientists for diverse applications. Our study focused on assessing GPT-4's capabilities in generating text, tables, and diagrams for biomedical review papers. We also assessed the consistency in text generation by GPT-4, along with potential plagiarism issues when employing this model for the composition of scientific review papers. Based on the results, we suggest the development of enhanced functionalities in ChatGPT, aiming to meet the needs of the scientific community more effectively. This includes enhancements in uploaded document processing for reference materials, a deeper grasp of intricate biomedical concepts, more precise and efficient information distillation for table generation, and a further refined model specifically tailored for scientific diagram creation.
GPT-4作为OpenAI大型语言模型的最先进版本，已引起广泛关注，迅速成为各个领域不可或缺的人工智能工具。这包括科学家对其进行的各种应用探索。我们的研究重点是评估GPT-4在为生物医学综述论文生成文本、表格和图表方面的能力。我们还评估了GPT-4在文本生成方面的一致性，以及使用该模型撰写科学综述论文时潜在的抄袭问题。基于这些结果，我们建议改进ChatGPT的功能，以更有效地满足科学界的需求。这包括改进上传文档以处理参考资料、更深入地理解复杂的生物医学概念、更精确高效地提炼信息以生成表格，以及进一步优化专门用于创建科学图表的模型。
