Xander Verbeek

Personalization session (Xander Verbeek will be presenting together with Ignace d'Hingh)14.30-16.00

Profile

Dr. Ir. Xander Verbeek is head of health informatics and data science at the Netherlands Comprehensive Cancer Organisation (IKNL). He and his team are tasked with the digital transformation of IKNL by;

  1. optimizing registration for the Netherlands Cancer Registry (NCR)
  2. new knowledge generation from NCR and (inter)national cancer registry data
  3. implementation of that knowledge in clinical practice

One of their first results include the development of (i) FAIR decision support services based on national clinical practice guidelines and prediction models (ii) an open source personal health train infrastructure (distributedlearning.ai) for distributed learning from international cancer registry data. Dr. Verbeek holds a PhD degree in biophysics, where he focused on cardiac mechanics and electrophysiology, and for which he received a grant from the Nederlandse Hartstichting. Before joining IKNL he worked for 10 years at Philips Health Informatics. He is a member of the expert council at Centrale Zorgverzekeraars, the steering committees of the ‘Health Deal Digital Ecosystem for Decision Support in Cancer’, GENONCO (GEnomics Portal for precision medicine research in ONCOlogy) and Registration aan de Bron. He is also a member of the scientific advisory boards at Evidencio and Pathology Imaging Exchange.

From FAIR data to FAIR knowledge – towards bridging the gap for clinical practice. 

Healthcare is confronted with a data-explosion. Adhering to FAIR data principles is an important pre-requisite for being able to exploit this data for new knowledge generation. But with this data-explosion, healthcare also needs to deal with an ever-growing amount of knowledge. For patients to benefit, innovative technology is required to support physicians to deal with this knowledge explosion. The Netherlands comprehensive cancer organisation (IKNL) responds to these challenges not only by applying FAIR principles to data but also to knowledge generated from that data. Therefore, IKNL has developed  (i) an open source personal health train infrastructure (distributedlearning.ai) for distributed learning from international cancer registry and other data, (ii) FAIR decision support resources and services (oncoguide) for data driven national clinical practice guidelines and prediction models.  

Presentation Xander Verbeek and Ignace d'Hingh (PDF)