IDEA4RC
Intelligent Ecosystem to improve the governance, the sharing and the re-use of health Data for Rare Cancers
Artificial Intelligence
https://cordis.europa.eu/project/id/101057048 ←Back to Research projects
Financing

Goals
The main objective of this project is to establish a Data Space for rare cancers (RC) that will make possible the re-use of existing multisource health data (cancer registry data, national registries, data from biobanks etc.) across European healthcare systems leveraging emerging interoperability technologies and AI approaches. The realized ""Rare Cancer Data Ecosystem"" is expected to improve the quality and the organization of RC patients care, and to increase knowledge on rare cancers advancing health research, so that all patients have equal access to high quality specialist care. The project approach will be experienced in the framework of the European reference network for rare adult solid cancers (EURACAN).
How is it achieved?
In this context, IDEA4RC leverages on rare cancer ERNs’ – in particular on EURACAN’s – wealth of data, on one side, and on emerging interoperability technologies and AI approaches for distributed data integration, federated analysis, and knowledge extraction from existing structured (e.g., EHRs, e-CRFs, Registries) and unstructured (e.g., clinician notes, image reports, pathology reports) health data on the other side, to improve the delivery of care, facilitate patients’ information and advance clinical and epidemiological research in rare cancers. The project ambition is to establish the framework for a first-in-the-field European Data Ecosystem for Rare Cancers, spanning multiple sources in multiple EU countries and supported by (i) a federation of interoperability “capsules” based on FHIR APIs; (ii) AI tools for multi-language data processing and analysis; (iii) a Multimodal Data Navigator to assist clinicians and researchers in finding and accessing available data of stipulated quality; and (iii) modern trust-building technologies (e.g. blockchain) to orchestrate data governance and incentivize data sharing and altruism. The developed tools will be experienced by relevant “data (re-)use pilot cases” across 11 reference Centers of the ERN EURACAN.
What was our contribution?
The University of Deusto will lead the Natural Language working group, who is in charge to create the NLP toolkit that will process the free text in the Electronic Health Records and transform it to structured data. This toolkit will be able to process documents in eight European languages. Deusto is also in charge of creating the FHIR compatible data and metadata models, which will ensure the FAIRification of the data stored in the federated infrastructure.
This project has received funding from the European Union’s Horizon Europe Research and Innovation Programme under Grant Agreement Nº GA 101057048