计算科学助力叙事医学人才培养的实践路径研究
Research on the Practical Pathways of Computational Science to Facilitate the Cultivation of Narrative Medicine Talents

文章主要探讨了计算科学助力叙事医学人才培养的实践路径。随着计算科学的快速发展，自然语言处理、生成式AI等计算科学的技术为叙事医学教育提供了许多智能化工具和量化分析方法，如基于深度学习的文本分析、生成式AI辅助写作等。基于此，论文构建了“计算科学 + 叙事医学”的跨学科培养框架，包含三大内容：贯穿医学教育全周期的课程体系、基于智能技术的教学工具开发、定量与定性结合的多维评估系统。同时指出技术应用中需要平衡量化分析与人文关怀，确保数据隐私安全。这种跨学科融合模式不仅能够提升叙事医学教学的科学性和标准化水平，还能通过智能化工具的应用增强教学效果的可测量性和可复制性，为构建新时代医学人文教育体系提供了创新性的解决方案。
This article mainly explores the practical path of using computational science to assist in the cultivation of narrative medicine talents. With the rapid development of computational science, technologies such as natural language processing and generative AI have provided many intelligent tools and quantitative analysis methods for narrative medical education, such as deep learning-based text analysis and generative AI-assisted writing. Based on this, the paper constructs an interdisciplinary training framework of “computational science + narrative medicine”, which includes three major contents: a curriculum system that runs through the entire medical education cycle, the development of teaching tools based on intelligent technology, and a multidimensional evaluation system that combines quantitative and qualitative methods. At the same time, it is pointed out that a balance between quantitative analysis and humanistic care is needed in technological applications to ensure data privacy and security. This interdisciplinary integration model not only enhances the scientific and standardized level of narrative medicine teaching, but also enhances the measurability and replicability of teaching effectiveness through the application of intelligent tools, providing innovative solutions for building a new era of the medical humanities education system.