October 25, 2021 | imec
Data-driven machine learning has emerged as a promising approach for building accurate and robust statistical models from medical data, which is collected in huge volumes by modern healthcare systems.
But most of these data are stored in “silos”. They reside at different hospitals and research centres, and are distributed across servers and databases. It’s a challenge to access all the relevant data needed to build powerful models.
Other types of valuable data – e.g., chemical compounds used for drug discovery and development – are usually kept in-house by pharma companies and are unlikely to be shared due to its competitive nature.
In this visionary seminar, we’ll talk about the potential usage of such data in the healthcare sector. We’ll discuss how data-sharing is being tackled at the European scale and how new technologies – e.g. Distributed or Federated Machine Learning – can enable data-sharing without giving up privacy. And we’ll see how Europe's regulations – e.g. the GDPR – tries to guarantee our privacy in all of this.
We foresee this event on a physical location - TBC
15h30: Registration with refreshments
16h20: Welcome by Leuven MindGate
16h30: Introduction by Wilfried Verachtert (IMEC), chairman of this event
16h40: The Use of Healthcare Data in the Life Sciences Industry
Bart Vannieuwenhuyse (J&J)
17h00: Multiple Sclerosis and the Use of Healthcare Data
Liesbet Peeters (UHasselt)
17h20: Better Use of Healthcare Data in Hospitals
Stephane Willaert (Robovision)
17h40: break with sandwiches & soup
18h00: Privacy Preserving Amalgamated Machine Learning
Roel Wuyts (IMEC-KUL)
18h20: ELIXIR & Distributed Infrastructure for Biological Data
Frederik Coppens (VIB – ELIXIR)
18h40: Health data & the GDPR
Hanne Elsen (UGent)
19h00: Debate with all speakers or Q&A
19h30: Networking and reception