Palindromo Consulting, Leuven, Belgium.
Leiden University Medical Center (LUMC), Radiology Department, Albinusdreef 2, 2333ZA, Leiden, the Netherlands.
Phys Med. 2021 Mar;83:174-183. doi: 10.1016/j.ejmp.2021.01.069. Epub 2021 Mar 31.
To provide a guideline curriculum related to Artificial Intelligence (AI), for the education and training of European Medical Physicists (MPs).
The proposed curriculum consists of two levels: Basic (introducing MPs to the pillars of knowledge, development and applications of AI, in the context of medical imaging and radiation therapy) and Advanced. Both are common to the subspecialties (diagnostic and interventional radiology, nuclear medicine, and radiation oncology). The learning outcomes of the training are presented as knowledge, skills and competences (KSC approach).
For the Basic section, KSCs were stratified in four subsections: (1) Medical imaging analysis and AI Basics; (2) Implementation of AI applications in clinical practice; (3) Big data and enterprise imaging, and (4) Quality, Regulatory and Ethical Issues of AI processes. For the Advanced section instead, a common block was proposed to be further elaborated by each subspecialty core curriculum. The learning outcomes were also translated into a syllabus of a more traditional format, including practical applications.
This AI curriculum is the first attempt to create a guideline expanding the current educational framework for Medical Physicists in Europe. It should be considered as a document to top the sub-specialties' curriculums and adapted by national training and regulatory bodies. The proposed educational program can be implemented via the European School of Medical Physics Expert (ESMPE) course modules and - to some extent - also by the national competent EFOMP organizations, to reach widely the medical physicist community in Europe.
为欧洲医学物理学家（MPs）的教育和培训提供与人工智能（AI）相关的指导课程。
拟议的课程分为两个层次：基础（向 MPs 介绍 AI 的知识支柱、发展和医学影像和放射治疗领域的应用）和高级。这两个层次都适用于各个亚专业（诊断和介入放射学、核医学和放射肿瘤学）。培训的学习成果以知识、技能和能力（KSC 方法）呈现。
对于基础部分，KSC 分为四个小节：（1）医学影像分析和 AI 基础；（2）在临床实践中实施 AI 应用；（3）大数据和企业影像；以及（4）AI 流程的质量、监管和道德问题。对于高级部分，则提出了一个共同的版块，由每个亚专业核心课程进一步详细阐述。学习成果也被转化为更传统格式的教学大纲，包括实际应用。
本 AI 课程是首次尝试在欧洲为医学物理学家创建扩展当前教育框架的指南。它应被视为一个文件，以补充各亚专业课程，并由国家培训和监管机构进行调整。所提出的教育计划可以通过欧洲医学物理专家学校（ESMPE）的课程模块实施，并且在一定程度上也可以通过国家有能力的 EFOMP 组织实施，以广泛覆盖欧洲的医学物理师社区。
