医学成像中的人工智能教育:一个范围审查
Su Jean Loi1, Wenhui Ng1, Christopher Lai1
1Singapore Institute of Technology, 10 Dover Drive, 138683, Singapore.
Journal of medical imaging and radiation sciences
|December 24, 2024
概括
人工智能 (AI) 培训对医学成像专业人员至关重要. 本文综合了当前的人工智能课程,强调需要扩展产品和基于证据的设计,以更好地将人工智能纳入医疗保健.
科学领域:
- 医疗成像医学成像
- 人工智能教育 人工智能教育
背景情况:
- 医疗保健正在快速整合人工智能 (AI),需要为临床成像人员提供专门培训.
- 在医学课程和针对成像专业人员的AI培训综合资源中,在正式的AI教育中存在很大的差距.
研究的目的:
- 为了回答这个问题:"对于临床成像人员,目前的AI培训计划或课程是什么?"
- 提供医疗成像中现有的AI教育计划的概述.
主要方法:
- 根据Arksey & O'Malley的框架和PRISMA指南进行范围审查.
- 从2023年6月到9月,搜索了六个电子数据库,涉及两个阶段的选过程.
- 使用标准化形式提取数据,根据主题和表格进行总结.
主要成果:
- 包括22项研究,重点是增强人工智能知识和成像人员的实践技能.
- 课程涵盖了人工智能基础到成像信息学,主要在线提供,时间长度和教学演示不同.
- 放射科医生是主要的目标受众;多学科团队开发了内容. 参与者的反是积极的,尽管有时间限制.
结论:
- 现有的AI课程旨在建立基础知识,技术技能和AI在成像中的实际应用.
- 未来的人工智能教育应该优先考虑基于证据的设计,扩展到放射科医生,增强成像信息学内容,并利用多样化的教学策略和资源.
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