AI and Health Data for Improving Cardiovascular Health and Related Non-Communicable Diseases

The initiative is built around two complementary and mutually reinforcing objectives. Together, they aim to establish the foundations of a European model for cardiovascular and related chronic disease care using artificial intelligence, based on high-quality health data and solutions validated by real clinical outcomes.

Objective 1 – Using health data for AI applications in cardiovascular and related chronic diseases.
The first objective is to organize, consolidate and provide access to high-quality health data across the EU to support the development, training, validation and implementation of artificial intelligence tools focused on cardiovascular and other non-communicable diseases (particularly diabetes and obesity). This must be aligned with the future application of the European Health Data Space (EHDS), which provides the regulatory and technical framework for secure, privacy-protected and interoperable secondary use of health data between member states.

Objective 2 – Implementing AI-based solutions for risk prediction, prevention, treatment and personalized healthcare.
The second objective involves identifying, validating and scaling mature AI applications capable of enhancing the effectiveness of risk prediction, early detection, personalized prevention, treatment and rehabilitation for cardiovascular and related chronic diseases.

Overall, the initiative aims to harness the potential of artificial intelligence and health data to accelerate early detection, prediction, personalized prevention, integrated treatment and rehabilitation of cardiovascular and related non-communicable diseases, including rare and complex forms.

Proposals must be submitted by a consortium consisting of at least 5 beneficiaries from 5 different eligible countries.

This initiative is expected to deliver tangible and scalable results that will facilitate the implementation of AI-based personalized healthcare for cardiovascular and related non-communicable diseases, while laying the foundations for a robust European data ecosystem for health innovations.

Expected results – data dimension:

• Creation of a large-scale, federated, high-quality dataset on cardiovascular and metabolic diseases, aligned with the EHDS framework. This dataset will be representative, inclusive and interoperable, enabling the development, training and comparative evaluation of AI tools across countries.
  
• Definition and implementation of minimum technical requirements for cardiovascular disease datasets, including structured phenotypes, genetic and biometric markers, as well as metadata quality labeling.
  
  

Expected results – AI implementation dimension:

• Validated AI-based solutions: a portfolio of artificial intelligence tools will be tested in real clinical settings with proven effectiveness for early detection, risk prediction and personalized prevention of cardiovascular and related chronic diseases.
  
• Implementation frameworks: the initiative will develop practical guidelines and protocols to facilitate the integration and scaling of AI applications across different healthcare systems. These will cover governance, interoperability, medical staff training, patient engagement and continuous performance monitoring.
  
• Strategic guidelines: publication of a roadmap and reference model for large-scale integration, providing recommendations to health authorities, hospitals and policymakers on responsible and sustainable implementation of AI tools, ensuring informed decision-making at national and European levels.
  
• Robust evidence base: the project will create comparative data on safety, effectiveness (e.g., sensitivity, specificity, cost-effectiveness), usability and user perception, which will form the basis for clinical practice and health policy.
  

Through the official European Commission resource – EU Funding & Tenders Portal