A European flagship initiative leveraging AI and health data for cardiovascular health and related non-communicable diseases: Advancing Risk Prediction, Prevention, Treatments, Personalised Care and Rehabilitation

• Improved health outcomes: Earlier diagnosis and more targeted prevention of NCDs, leading to reduced disease progression, complications, and avoidable mortality.
• Greater equity: Enhanced access to personalised diagnostics and AI-supported care pathways, especially in underserved regions or Member States with limited innovation capacity.
• Efficiency and sustainability of health systems: Better use of resources through predictive and preventive approaches, reducing the burden of chronic conditions on healthcare infrastructures.
• Trust in European health AI: By ensuring compliance with data protection, safety, and transparency standards, the initiative will foster trust in the responsible use of AI for health in line with the AI Act and EHDS Regulation. It will also support the uptake — and where relevant, the development — of specifications and standards foreseen under both frameworks, notably for interoperability, risk management and data governance

This initiative is expected to generate tangible, scalable results supporting the adoption of AIdriven personalised care for cardiovascular diseases and related non-communicable conditions, while laying the foundations of a trusted European data ecosystem for health innovation.

Expected results – Data dimension

• Creation of a large-scale, federated, high-quality dataset for cardiovascular and metabolic diseases, aligned with the EHDS framework. This dataset will be representative, inclusive, and interoperable, and will enable the development, training and benchmarking of AI tools across borders.
• Definition and uptake of minimum technical specifications for cardiovascular datasets, including structured phenotypes, genetic and biometric markers, and metadata quality labelling.

Expected results – AI adoption dimension

• Validated AI solutions: A portfolio of AI tools will be piloted in real-world clinical settings, with demonstrated effectiveness in early detection, risk prediction, and personalised prevention of cardiovascular and related chronic diseases.
• Deployment frameworks: The initiative will produce practical guidelines and protocols to facilitate the integration and scale-up of AI applications across diverse healthcare systems. These will cover governance, interoperability, clinician training, patient engagement, and continuous performance monitoring.
• Strategic guidance: The publication of a roadmap and a blueprint for large-scale integration will inform health authorities, hospitals, and policymakers on how to responsibly and sustainably adopt AI tools, supporting informed decisions at national and Union levels.
• Robust evidence base: The project will generate comparative data on safety, performance (e.g. sensitivity, specificity, cost-effectiveness), usability and acceptability, informing both clinical practice and health policy.

The initiative is structured around two complementary and mutually reinforcing objectives. Together, they aim to lay the foundations for a European model of AI-enabled cardiovascular and comorbid chronic disease care, grounded in high-quality health data and real-world validated solutions.

Objective 1 — Leveraging Health Data for AI Applications in Cardiovascular and Related Chronic Diseases The first objective is to structure, federate, and enable access to high-quality health data across the Union to support the development, training, validation, and deployment of AI tools focused on cardiovascular diseases and related non-communicable diseases (such as diabetes and obesity). This will align with and prepare for the future application the EHDS, which provides the regulatory and technical framework to enable the secure, privacy preserving, and interoperable secondary use of health data across Member States.

Objective 2 — Deploying AI Solutions for Risk Prediction, Prevention, Treatments, and Personalised Care The second objective is to identify, validate, and scale up mature AI applications capable of improving the risk prediction, early detection, personalised prevention, treatment, and rehabilitation of cardiovascular and related chronic diseases.

This initiative aims to leverage AI and health data to accelerate the early detection, prediction, personalised prevention, integrated management and rehabilitation of CVDs and related NCDs, including rare and complex forms.