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Automate Curation and Publishing of
Personal Health Data Through Artificial Intelligence

Aim and Objectives

All available personal health data of an individual in one consistent semantic model: AIDAVA will develop a digital solution, orchestrating diverse artificial intelligence technologies, for more efficient curation and publishing of personal health data, delivering interoperable and reusable personal health records for the benefit of patients and clinical researchers.

The European Commission has set itself an ambitious goal: by 2030 citizens shall have full possession of their data, including health data, and have the necessary skills for making competent decisions about that data. However, reuse of personal health care data is particularly difficult as each individual’s data is typically scattered across different clinics, surgeries or hospitals and, increasingly, across providers of medical devices and personal health apps. In addition, much information is still in paper and in narrative form. Despite attempts to streamline and modernise health data management systems, seamless access and use of high-quality and integrated personal health data remains challenging for individual patients, health care providers, researchers, public health authorities and national insurances across Europe.

Additionally, the data curation and publishing process of legacy data keeps being costly, time-consuming and manageable only by experts. As a consequence, much of the available personal health data is neither curated nor reusable for advanced algorithms supporting preventive and personalised medicine and clinical research; an unfortunate situation considering the wealth of information personal health data holds for entire healthcare systems.

AIDAVA sets out for a quantum leap in automating personal health data curation and publishing by orchestrating multiple Artificial Intelligence (AI)-based solutions.

AIDAVA Objectives

  1. Increase the reusability of different types of Personal Health Data

    • Maximising automation of data curation & publishing of personal health data through metadata on data sources and access to multiple AI tools.
    • Facilitate individuals' involvement through an AI conversational assistant, adapted to the literacy level of the individual.
  2. Test the solutions in two use cases

    • Maintain a EU wide breast cancer registry, federated across three centres in three countries with different languages.
    • Monitor cardiovascular patients at risk of myocardial infarction thanks to their holistic personal longitudinal health record.