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 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.

Start date
01 September 2022

Duration
4 years

Participants
14 institutions from 9 countries

Horizon Europe Funding
€7.72 million

Egnosis’ Budget
€779,687

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