Integrated, high-quality personal health data (PHD) represents a potential wealth of knowledge for health care 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 computable knowledge derived from unstructured and structured, heterogeneous data. The assistant includes a backend with a library of AI-based data curation tools and a frontend based on human-AI interaction modules that will help users when automation is not possible, while adapting to users’ preferences. The exceptional interdisciplinary team of 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.
The AIDAVA team will work around four technology pillars:
- 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.
- In the long-term, AIDAVA has the potential to democratise participation in data curation & publishing by citizens/patients leading to overall savings in health care costs (through disease prevention, early diagnosis, personalised medicine) and supporting delivery of the European Health Data Space.
AIDAVA will test its solution in two use cases. Learn more.