Navigating the Gap Between Technical Progress and Clinical Impact
Cardiovascular diseases remain the leading cause of death in the European Union, claiming over 1.7 million lives each year and imposing a substantial economic burden on health systems and societies. One in five of these deaths is considered preventable. As Europe's population ages, this burden is projected to intensify, placing growing pressure on health systems already facing workforce shortages and constrained budgets. Artificial intelligence presents an opportunity to change this trajectory.
This report examines the current state of AI across the cardiovascular care continuum, from prevention and early risk prediction through detection, diagnosis, personalised treatment, and health system optimisation. It assesses the maturity and evidence base of key applications, identifies the bar-riers to wider adoption, and proposes policy priorities for the European Union.
The evidence reviewed points to real progress in a number of domains. AI-assisted echocardiography, automated ECG interpretation, coronary CT-derived fractional flow reserve, and AI-supported stroke triage are among the applications with the strongest validation and the clearest demonstrated benefit in routine clinical practice. Other applications, including wearable-based risk detection, AI-guided screening for undiagnosed atrial fibrillation, and machine learning approaches to personalised treatment selection, show considerable promise but require more rigorous prospective evalua-tion before broad deployment can be recommended.
Across the field, a persistent gap exists between technical performance and demonstrated clinical impact. Most AI tools have been evaluated on accuracy metrics rather than on whether their use improves patient outcomes, and independent external validation remains limited. Adoption is uneven, concentrated in well-resourced academic centres, while smaller hospitals and less affluent health systems often lack the infrastructure, workforce capacity, and financing mechanisms needed to implement and sustain these tools.
Consumer-facing AI is already shaping how millions of Europeans engage with their cardiovascular health, largely outside any clinical governance framework, creating challenges that require urgent policy attention.
The EU has built a strong regulatory and data governance foundation through the AI Act, the Medical Devices Regulation, and the European Health Data Space. Realising the potential of AI in cardiovascular care will require translating these frameworks into practical support for validation, implementation, and equitable access. Key priorities include strengthening post-market surveillance, investing in data infrastructure and workforce readiness, directing implementation support toward under-resourced settings, and requiring demonstration of clinical utility rather than technical performance alone as the standard for adoption.
Cardiovascular care offers an ideal domain in which to establish the conditions for responsible AI deployment in healthcare. Lessons learned here, on evidence generation, regulatory harmonisation, equitable access, and clinical integration, will be transferable across the broader landscape of non-communicable diseases that account for most of the health burden in Europe.
COMTE Valentin;
CAMARA Oscar;
BIJNENS Bart;
FRASER Alan;
MEERSMANS Karen;
ZANI Alessandro;
BERTOLINI Lorenzo;
RUIZ SERRA Victoria;
STILIANAKIS Nikolaos;
GRIESINGER Claudius Benedict;
PANIDIS Dimitrios;
AMATO Ottavia;
HATZARAS Kyriacos;
MESTRE GASCON Antoni;
ZANCA Federica;
BERNAUX Mélodie;
OLIVEIRA Andreia;
CERESA Mario;
QUERCI Maddalena;
WIESENTHAL Tobias;
2026-04-07
Publications Office of the European Union
JRC146049
978-92-68-38945-4 (online),
1831-9424 (online),
EUR 40690,
OP KJ-01-26-159-EN-N (online),
https://publications.jrc.ec.europa.eu/repository/handle/JRC146049,
10.2760/4314186 (online),
