In order to be able to use artificial intelligence (AI) in medicine without scepticism and to recognise and assess its growing potential, a basic understanding of this topic is necessary among current and future medical staff. Under the premise of "trust through understanding", we developed an innovative online course as a learning opportunity within the framework of the German KI Campus (AI campus) project, which is a self-guided course that teaches the basics of AI for the analysis of medical image data. The main goal is to provide a learning environment for a sufficient understanding of AI in medical image analysis so that further interest in this topic is stimulated and inhibitions towards its use can be overcome by means of positive application experience. The focus was on medical applications and the fundamentals of machine learning. The online course was divided into consecutive lessons, which include theory in the form of explanatory videos, practical exercises in the form of Streamlit and practical exercises and/or quizzes to check learning progress. A survey among the participating medical students in the first run of the course was used to analyse our research hypotheses quantitatively.
翻译:为了能够在医学上不持怀疑态度地使用人工智能(AI),并认识和评估其日益增长的潜力,目前和未来的医务人员必须基本了解这一专题。在“通过理解信任”的前提下,我们开发了一个创新的在线课程,作为德国KI校园(AI校园)项目框架内的学习机会,这是一个自导课程,教授AI用于分析医学图像数据的基本知识。主要目标是提供一个学习环境,在医学图像分析中充分理解AI,以便进一步激发人们对这个主题的兴趣,并通过积极应用经验来克服对它使用的限制。重点是医疗应用和机器学习的基本原理。在线课程分为连续课程,包括解释性录像、斯特雷姆利特实际练习和/或测验等形式的理论,以检查学习进度。在参加课程第一阶段的医科学生中进行的一项调查,用来从数量上分析我们的研究假设。