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With the rapid development of computer software and hardware, more and more health data are becoming available. However, collecting and reusing this is often challenging because in many cases it involves privacy-sensitive personal data.
Federated learning makes it possible to train AI models without anyone seeing or touching your data, and provides a way to unlock information to feed new AI applications. This holds great promise for connecting fragmented data sources in healthcare while maintaining privacy.
In this new DASH webinar, taking place on November 8 from 4.30 to 5.30 pm, we have invited Siemens Healthineers to talk more about this promising approach. In the second part of the webinar, we take a closer look at Federated Learning within the UMCG.
Programme
- 16.30-16.35 Introduction by Peter van Ooijen
- 16.35 - 17.00 ‘Enabling scalable Medical Imaging AI with Federated Learning’ by Dr Anna Jerebko, Head of Clinical conditions and workflow, Digital & Automation at Diagnostic Imaging, Siemens Healthineers.
- 17.00 – 17.20 Federated Learning within the UMCG by Erfan Darzidehkalani
- 17.30 – 17.30 Q&A
This webinar has already taken place. You can find the recording on our YouTube channel.
