Proposals should address all of the following aspects:

• Developing robust novel solutions compliant with legal requirements that will improve the quality, interoperability, machine-readability and re-use of health data and metadata in compliance with FAIR data management principles, making these data more accessible to clinicians, researchers and citizens. The focus should be on data in electronic health records (EHRs) and/or patient registries, taking into account the Commission Recommendation on a European Electronic Health Record exchange format.
• Developing innovative natural language processing tools, including computational semantics, ontologies, text mining, associated machine learning and deep learning, to improve accessibility, interoperability, translation, transcription, and analysis of health data (e.g. to predict risks). Tools should extract health information from unstructured data in different clinical and medical sources, and bring that data into EHRs/patient registries in a structured form. The innovative solutions should also address missing data in EHRs and/or patient registries and their related metadata, to reduce bias and improve the quality of conclusions.
• Developing and piloting AI-powered virtual assistants that will utilise the tools and solutions developed (as mentioned above) in order to demonstrate improved usability of health data for end-users.

Proposals are expected to build on and contribute to existing European and international data standards, specifications and schemas for health data.
Applicants should focus on health data coming from a number of EU Member States and EEA countries, constituting as much as possible a representative sample of the European healthcare landscape, so as to contribute to the work on the creation of the European Health Data Space.

The developed solutions should be quick and easy to use by researchers and clinicians.