开发加拿大的人工智能医学课程,使用Delphi研究
Rohit Singla1,2, Nikola Pupic3, Seyed-Aryan Ghaffarizadeh3
1MD/PhD Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. rsingla@ece.ubc.ca.
NPJ digital medicine
|November 18, 2024
概括
人工智能 (AI) 教育对未来的医生至关重要. 专家们为加拿大医学学生开发了一套人工智能课程,确定了有效整合医疗技术的必要能力.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 课程开发 课程开发
背景情况:
- 将人工智能 (AI) 教育融入医疗课程中,对于准备未来医疗保健专业人员至关重要.
- 医疗专业人员越来越需要了解和利用AI技术在临床实践中.
- 加拿大本科医学教育需要对AI能力发展采取结构化的方法.
研究的目的:
- 为加拿大本科医学学生建立基于专家的人工智能 (AI) 课程.
- 确定医疗教育中必不可少的AI学习能力.
- 为将人工智能能力纳入现有医学课程提供建议.
主要方法:
- 为了在专家之间达成共识,采用了德尔菲方法.
- 一个由18名加拿大卫生和人工智能专家组成的小组参加了三轮调查.
- 在伦理学,法律,理论,应用,沟通,协作和质量改善方面确定了课程的关键组成部分.
主要成果:
- 医疗教育工作者和专业人士对全面的人工智能教育提供了大量支持.
- 在107个确定的课程能力中,有82个被认为是临床和教育优先事项的基本能力.
- 该研究确定了医学生人工智能能力发展的关键领域.
结论:
- 开发的AI课程为提高医学学生的AI素养提供了一个框架.
- 认可的能力将使未来的医疗保健专业人员能够有效地使用人工智能技术.
- 整合人工智能教育对于推进医疗保健质量和创新至关重要.
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