Die Anwendung von künstlicher Intelligenz (KI) im Rahmen des maschinellen Lernens ist oft mit Nutzung großer Datenmengen verbunden, die leistungsfähige Rechen- und Dateninfrastrukturen
benötigen. Gesundheitsdaten stellen eine besondere Herausforderung dar. Der Beitrag zeigt auf, wie es trotzdem gelingen kann, auf europäischer Ebene einen sicheren und effektiven Umgang mit
Daten für die Nutzung in KI aufzubauen, und wo noch Probleme bestehen.
Abstract
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.
Schlüsselwörter
künstliche Intelligenz - KI - Forschungsdaten - Datenmanagement - Datenschutz
Keywords
artificial intelligence - AI - research data - data management - data protection
