人工智能教育:为消费者,翻译人员和开发人员提供基于证据的医学方法
Faye Yu Ci Ng1, Arun James Thirunavukarasu2, Haoran Cheng3
1Artificial Intelligence and Digital Innovation, Singapore Eye Research Institute, Singapore National Eye Center, Singapore Health Service, Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
Cell reports. Medicine
|October 18, 2023
概括
医疗保健专业人员需要人工智能 (AI) 培训,以有效地整合这项技术. 一项拟议的课程将临床医生归类为人工智能消费者,翻译人员或开发人员,增强医学教育和患者护理.
科学领域:
- 医学教育 医学教育
- 医疗保健中的人工智能
- 医疗信息学 医疗信息学
背景情况:
- 医疗保健专业人员缺乏足够的培训,以加强人工智能 (AI) 的整合.
- 现有的医学教育框架需要适应,以整合人工智能能力.
- 基于证据的医学 (EBM) 提供了一个将新科学进展纳入实践的模型.
研究的目的:
- 为医疗保健中人工智能 (AI) 教育提出一个核心课程.
- 将临床医生分类为角色:人工智能的消费者,翻译者和开发者.
- 突出AI和EBM在医学教育中的关系.
主要方法:
- 将临床医生概念化为人工智能消费者,翻译者或开发者.
- 概述人工智能教育的核心课程.
- 识别人工智能课程实施的障碍.
主要成果:
- 基于临床医师角色 (消费者,翻译者,开发者) 的人工智能教育的分层方法.
- 在现有的医疗课程中整合AI教育的整合策略.
- 识别障碍,包括时间,资源,可变的兴趣和知识保留.
结论:
- 提高人工智能素养和熟练的劳动力可以加速医疗保健创新.
- 定制的人工智能教育对于医疗保健中有效采用技术至关重要.
- 解决实施障碍是成功将人工智能整合到医疗培训中的关键.
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