AI-powered Solutions to Personalized Healthcare Using Knowledge Graphs
Remzi Celebi, Assistant Professor at the Maastricht University Institute of Data Science and technical co-coordinator for the AIDAVA project, was interviewed by Ontotext to discuss how Artificial Intelligence, data curation automation and knowledge graphs are used to give patients more control of their health data.
AIDAVA (short for AI-powered Data Curation & Publishing Virtual Assistant) is a Horizon Europe project, which brings together 14 partners from 9 EU countries. Their shared goal is to maximize automation in the curation and publishing of heterogeneous and scattered personal health data with the support of the patients while minimizing their input. The end goal is to give control of health data to patients so that they can build a comprehensive, interoperable, and reusable health medical record, which they can share with their treating physician anytime, anywhere. On top of that, they can also share it with external stakeholders for research and policy-making – typically referred to as the “common good” – and contribute actively, in a data privacy compliant way, to the emerging European Health Data Space.