The European Society of Cardiology (ESC) announced CHAIN on 7 October 2026. Co-funded through the EU4Health programme and coordinated by the ESC, the €20 million project will assess six applications for cardiovascular care. It will examine where AI can support prevention and treatment, including early detection, and what conditions are needed for safe, useful clinical practice. Hospitals in 13 countries will assess the tools in clinical settings while keeping personal health data under local control.
CHAIN has 53 partners from 20 countries. The consortium brings together hospitals and universities, as well as research centres. Technology companies and health authorities are involved, alongside patient organisations. Spain’s Centro Nacional de Investigaciones Cardiovasculares Carlos III, or CNIC, is among the partners. The 20-country membership is separate from the 13 countries where the clinical scenarios will be assessed.
Algorithm performance is only part of the test.
CHAIN will examine clinical usefulness and fairness, along with transparency and ease of use. It will also check whether the tools work consistently across patient groups and healthcare settings. Use cases range from cardiovascular risk prevention and stratification to early disease detection and clinical decision support. The project will also focus on managing complex cardiovascular conditions. It runs for 36 months and aims to build shared European infrastructure for evaluating AI in cardiovascular care.
That infrastructure, CardioData@EU, is designed as a federated environment aligned with the European Health Data Space. It will connect hospitals and clinical registries in different countries for evaluation, while drawing on other health-data sources. Personal health data will stay under local control rather than being gathered in a central database. Researchers will be able to compare tools across populations without moving the underlying records.
CHAIN also plans a European repository of validated AI solutions. Each tool will have an «AI passport» describing its performance and safety, and its suitability for clinical use. Hospitals, clinicians and health authorities could use that evidence to judge which systems fit their needs. The project aims to support safe, effective AI use, while leaving clinical decision-making to clinicians.
For CNIC, the work starts with the foundations needed to compare systems. The centre will contribute to shared data standards and interoperability, with data quality also on the agenda. Coordinated by Héctor Bueno and Fátima Sánchez-Cabo, the CNIC team will join a work package led by the University of Luxembourg. It will develop common clinical definitions and data-quality indicators, then set technical and security specifications for connecting institutions.
Inconsistent records can undermine comparisons between hospitals or patient groups. Common criteria should help researchers identify bias and test whether algorithms produce consistent results across populations. CHAIN plans to run its assessments in varied clinical settings across participating countries.
The ESC says CHAIN aims to make cardiovascular care safer and more equitable through reliable AI. CNIC scientific director Borja Ibáñez has said the centre will bring scientific rigour to the evaluation of tools designed to support prevention. Patient care is part of that work, too.
Outcome measures are also under debate in Spain’s thyroid cancer care. AECAT has called for assessments to account for lasting symptoms and patients’ ability to return to everyday life.
CHAIN will build on existing ESC initiatives such as EuroHeart and contribute to the EU’s Safe Hearts Plan. Its three-year programme includes a shared roadmap for evaluating and adopting AI in cardiology. Clinical assessments will take place across 13 countries.
