Abstract:

Objective To construct a nursing informatics intelligent question-answering system based on generative artificial intelligence and conduct preliminary study for applying and testing. Methods Data was collected using web crawling technology to build a nursing informatics knowledge base，enhancing the reliability of the content output by the DeepSeek-V3 model. The system functions were integrated using the fastGPT platform to develop the nursing informatics intelligent question-answering system，and experimental testing was conducted. From April to May 2025，30 nursing students were recruited to evaluate the system’s usability and satisfaction through questionnaires and semi-structured interviews. Results Experimental test results showed that compared to Deep-Seek-V3，the nursing informatics intelligent question-answering system improved answer accuracy by 15.39% and semantic similarity by 3.08%. Students expressed positive attitudes and consistent opinions regarding interface clarity，system usability，answer accuracy，and reliability，with an average satisfaction score of（4.33±0.48） point. Besides，interview results indicated that the system could improve knowledge acquisition efficiency and facilitates better understanding of nursing informatics research trends and academic exchange information. However，there was still room for improvement in terms of the content of the knowledge base and system functionality. Conclusion The nursing informatics intelligent question-answering system demonstrates good effectiveness and usability. In the future，it can be further implemented in nursing education to promote the digital and intelligent transformation of nursing education and enhance teaching quality.

Key words: Generative artificial intelligence, Nursing education, Nursing informatics, Intelligent question-answering system