Seminar with Lea Köttering

Data Protection Legal Framework of Machine Learning Systems in Radiology

Abstract

The development and use of machine learning systems in the healthcare sector promises significant increases in efficiency and quality. In particular, the field of radiology is very advanced. However, machine learning systems require a huge amount of datasets, the models are considered as black boxes and can detect patterns in the data that humans cannot name in advance. These characteristics seem to collide especially with the principles of data minimisation, transparency and purpose limitation enshrined in the General Data Protection Regulation (GDPR). In this presentation, Lea Köttering will analyse to what extent the development and use of machine learning systems in radiology is compatible with the GDPR.

Registration 

Please register no later than the 18 May 2022 at 10:00 CEST using this registration form

Bio

Lea Köttering is a PhD candidate at the University of Hamburg (Germany). Her primary research interests lie in the interdisciplinary interface of machine learning, law and medicine. She studied law at the University of Hamburg (Dipl.-Jur.) and is working as a research assistant for Prof. Dr. Hans-Heinrich Trute from the University of Hamburg in the field of media and public law with a special focus on questions of digitisation. In this context she is involved in cooperation projects and research groups with the University Medical Centre Hamburg-Eppendorf (Germany), the Faculty of Computer Science at the University of Hamburg and the Institute for Artificial Intelligence in Medicine at the University of Essen (Germany).