脏学教育中的Vibe编码:由临床医生领导的,人工智能辅助的开源交互式学习工具的开发
Francesco Pesce1,2, Wisit Cheungpasitporn3
1Division of Renal Medicine, Ospedale Isola Tiberina - Gemelli Isola, Rome, Italy.
Renal failure
|November 7, 2025
概括
该Vibe编码框架使用人工智能从临床算法快速创建交互式脏学教育工具. 这种临床医生主导的方法将静态内容转化为可访问的,开源的数字学习资源.
科学领域:
- 医疗教育 技术 技术 医学教育
- 数字健康数字健康
- 腎病學培訓 腎病學培訓
背景情况:
- 医学教育中的数字工具往往是被动的,基于文本的.
- 需要有互动和引人入胜的教育资源,捕捉临床推理.
- 该Vibe编码框架旨在通过将专家决策融入数字工具来弥补这一差距.
研究的目的:
- 展示Vibe编码框架在科培训中的应用.
- 快速开发开源,人工智能辅助,基于网络的教育应用程序.
- 将静态的医学教育材料翻译成交互式,可访问的数字工具.
主要方法:
- 采用了一个结构化的,由医生领导的,人工智能辅助的开发过程.
- 这涉及到解构临床算法,使用自然语言与大型语言模型代码生成,并代UI改进.
- 源内容来源于同行评审的脏学教育文献.
主要成果:
- 四个开源的,基于网络的应用程序被成功开发:脏石 Navigator,NephroFlow CKRT 临床副驾驶员,脏管状酸化诊断助手和体积障碍的交互指南.
- 这些工具反映了专家的推理,包括自动计算,并在GitHub上发布,供全球教育使用.
- 该Vibe编码框架使得这些交互式工具的快速创建成为可能.
结论:
- 临床医生主导的,人工智能辅助的开发对于创建交互式医学教育工具是有效的.
- 该Vibe编码框架提供了一个可扩展和可重复的模型,用于医疗教育的创新.
- 这种方法支持脏病学领域的透明数字奖学金,并增强学员和教育工作者的学习能力.
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