从技术采用者到创造者:利用人工智能辅助的振动编码来改变临床教学和学习
Minyang Chow1,2, Olivia Ng1
1Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore.
Medical teacher
|April 9, 2025
概括
教育人员现在可以使用人工智能辅助的无代码工具创建定制的临床学习模拟. 这种方法增强了诊断推理和代谢动力学培训,提高了医学教育的可访问性和可扩展性.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 基于模拟的学习
背景情况:
- 将理论知识与实际临床技能相结合,是医学教育的一个持续挑战.
- 传统的教学方法不足以为临床医生准备复杂的决策和启发式开发.
- 需要可访问的工具来创建动态的临床学习体验.
研究的目的:
- 引入振动编码,一种人工智能辅助的无代码方法,用于教育工作者开发定制的临床模拟.
- 展示两个不同的模拟应用程序的创建和实用性:差异诊断培训器 (DDT) 和胰岛素和血糖模拟 (IBSS).
- 突出人工智能驱动的无代码平台在医疗模拟开发中的好处.
主要方法:
- 开发了vibe编码,一个人工智能辅助的无代码平台,使教育工作者能够通过对话提示创建模拟.
- 利用人工智能驱动的无代码平台,快速进行原型设计和学习工具的代改进.
- 应用了构建差异诊断训练器 (DDT) 和胰岛素和血糖模拟 (IBSS) 的方法.
主要成果:
- 振动编码允许教育工作者在没有编程专业知识的情况下创建交互式,可定制的临床模拟.
- DDT和IBSS在可访问性,成本效益和可扩展性方面取得了显著的改善.
- 该方法将重点从技术限制转移到教学目标,促进教育工作者的创造力.
结论:
- 由人工智能驱动的无代码平台使教育工作者成为创新临床模拟的创造者.
- 这种方法改变了医学学习经验,增强了诊断推理和临床判断.
- 开发可扩展,个性化的模拟最终改善了患者护理结果.
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