Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
School of Business and Economics, KIN Center for Digital Innovation, Vrije Universiteit Amsterdam, De Boelelaan 1105, VU Main Building A-wing, 5th floor, 1081 HV, Amsterdam, The Netherlands.
Eur Radiol. 2021 Aug;31(8):6021-6029. doi: 10.1007/s00330-020-07621-y. Epub 2021 Feb 15.
The aim is to offer an overview of the existing training programs and critically examine them and suggest avenues for further development of AI training programs for radiologists.
Deductive thematic analysis of 100 training programs offered in 2019 and 2020 (until June 30). We analyze the public data about the training programs based on their "contents," "target audience," "instructors and offering agents," and "legitimization strategies."
There are many AI training programs offered to radiologists, yet most of them (80%) are short, stand-alone sessions, which are not part of a longer-term learning trajectory. The training programs mainly (around 85%) focus on the basic concepts of AI and are offered in passive mode. Professional institutions and commercial companies are active in offering the programs (91%), though academic institutes are limitedly involved.
There is a need to further develop systematic training programs that are pedagogically integrated into radiology curriculum. Future training programs need to further focus on learning how to work with AI at work and be further specialized and customized to the contexts of radiology work.
• Most of AI training programs are short, stand-alone sessions, which focus on the basics of AI. • The content of training programs focuses on medical and technical topics; managerial, legal, and ethical topics are marginally addressed. • Professional institutions and commercial companies are active in offering AI training; academic institutes are limitedly involved.
旨在概述现有的培训计划，并对其进行批判性分析，为放射科医生的人工智能培训计划的进一步发展提出途径。
对 2019 年和 2020 年（截至 6 月 30 日）提供的 100 个培训计划进行演绎主题分析。我们根据培训计划的“内容”、“目标受众”、“讲师和提供代理”以及“合法化策略”来分析公共数据。
有许多面向放射科医生的人工智能培训计划，但其中大多数（80%）是短期的独立课程，不属于长期学习轨迹的一部分。培训计划主要（约 85%）侧重于人工智能的基本概念，并以被动模式提供。专业机构和商业公司积极提供这些计划（91%），而学术机构的参与则有限。
需要进一步开发系统的培训计划，这些计划在教育学上与放射学课程相结合。未来的培训计划需要进一步专注于学习如何在工作中使用人工智能，并进一步专业化和定制到放射科工作的背景。
大多数人工智能培训计划是短期的独立课程，侧重于人工智能的基础知识。
培训计划的内容侧重于医学和技术主题；管理、法律和道德主题仅略有涉及。
专业机构和商业公司积极提供人工智能培训；学术机构的参与有限。
