Medical care through optimised health data management

AI-powered DAta curation & publishing Virtual Assistant

Integrated, high-quality personal health data (PHD) represents a potential wealth of knowledge for healthcare systems, but there is no reliable conduit for this data to become interoperable, AI-ready and reuse-ready at scale across institutions, at national and EU level.

AIDAVA will fill this gap by prototyping and testing an AI-powered, virtual assistant maximising automation of data curation & publishing of unstructured and structured, heterogeneous data.

During this work, the consortium will develop and test two versions of this virtual assistant with hospitals and emerging personal data intermediaries, around breast cancer patient registries and longitudinal health records for cardio-vascular patients, in three languages.

AIDAVA can play a major role in preventive care (longitudinal health record of cardiovascular patients at risk of sudden cardiac arrest) and in making the treatments more effective (breast cancer registries federated across hospitals).


The AIDAVA project is based on four technology pillars:

  • Automation of quality enhancement and FAIRification of collected health data, in compliance with EU data privacy;
  • Knowledge graphs with ontology-based standards as universal representation, to increase interoperability and portability;
  • Deep learning for information extraction from narrative content; and
  • AI-generated explanations during the process to increase users’ confidence

By increasing automation of data quality enhancement, AIDAVA will decrease the workload of clinical data stewards; by providing high-quality data, AIDAVA will improve the effectiveness of clinical care and support clinical research.

The Role of Egnosis

The main contributions of Egnosis in this project are designing and developing an AI-powered virtual assistant, maximising automation of data curation & publishing unstructured and structured, heterogeneous data.

The assistant incorporates a back-end with a library of AI-based data curation tools and a front-end based on human-AI interaction modules while adapting to user preferences.

Project data

Start date: 01 September 2022

Duration: 4 years

Horizon Europe Funding: €7.72 million

Egnosis’ Budget: €779,687


Project coordinator: University of Maastricht (Netherlands)

Participants: 14 institutions from 9 countries


Check it out on Cordis!


This project has received funding from the European Union’s Horizon Europe research and innovation programme  under grant agreement No 101057062.

Isabelle de Zegher

My dream: To have all health data of a patient stored in a potentially gigantic personal health knowledge graph managed by the patient or by their deputy. Each patient would have a “data intermediary “ (per Data Governance Act) managing their PHKG, similar to how a bank manages their money, and would be able to use this data for their own benefit such as personalized medicine – and share this data for the common good.

Isabelle de Zegher
clinical co-coordinator for the AIDAVA project and founder of b!loba