Using GPT-4 to write a scientific review article: a pilot evaluation study

作者：Zhiping Paul Wang, Priyanka Bhandary, Yizhou Wang, Jason H. Moore · 发表于：BioData Mining · 年份：2024 · DOI：10.1186/s13040-024-00371-3 · 被引用次数：19 · 研究领域：Artificial Intelligence in Healthcare and Education、Topic Modeling、Meta-analysis and systematic reviews

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.