Fritsch Sebastian, Maassen Oliver, Riedel Morris
Anasthesiol Intensivmed Notfallmed Schmerzther. 2022 Mar;57(3):172-184. doi: 10.1055/a-1423-8052. Epub 2022 Mar 23.
The application of artificial intelligence (AI) is often associated with the use of large amounts of data for the construction of AI models and algorithms. This data should ideally comply with the FAIR Data principles, i.e. being findable, accessible, interoperable and reusable. However, the handling of health data poses a particular challenge in this context. In this article, we highlight the challenges of the data usage for AI in medicine using the example of anaesthesia and intensive care medicine. We discuss the current situation but also the obstacles for a wider application of AI in medicine in Europe and give suggestions how to solve the different issues. The article covers different subjects like data protection, research data infrastructures and approval of medical products. Finally, this article shows how it can nevertheless be possible to establish a secure and at the same time effective handling of data for use in AI at the European level despite its unneglectable difficulties.
人工智能（AI）的应用通常与使用大量数据来构建AI模型和算法相关联。理想情况下，这些数据应符合FAIR数据原则，即可发现、可访问、可互操作和可重复使用。然而，在这种情况下，健康数据的处理带来了特殊挑战。在本文中，我们以麻醉和重症医学为例，突出了医学中AI数据使用的挑战。我们讨论了当前的情况以及AI在欧洲医学中更广泛应用的障碍，并给出了解决不同问题的建议。本文涵盖了数据保护、研究数据基础设施和医疗产品审批等不同主题。最后，本文表明，尽管存在不可忽视的困难，但在欧洲层面仍有可能建立一种安全且同时有效的数据处理方式，以供AI使用。
