28 October 2026
HT will lead one of six use cases in the European collaboration, validating a generative AI model to support cardiovascular prevention across different healthcare settings.
Human Technopole is part of CHAIN — the European Cardiovascular Health Data and AI Network, a three-year initiative bringing together 53 partners from 20 countries to support the safe, effective and scalable use of artificial intelligence in cardiovascular care. Coordinated by the European Society of Cardiology and co-funded by the European Union’s EU4Health Programme, the project was launched on 7–8 October 2026 in Sophia Antipolis, France.
HT contributed to the core team that developed the project proposal and will lead Use Case 1, focused on validating a generative AI model for cardiovascular risk prediction. The use case will explore how AI can support both primary prevention, before cardiovascular disease develops, and secondary prevention, aimed at reducing the risk of further events in people with established disease. Working with European research and clinical partners the team, led by Emanuele di Angelantonio Head of the Health Data Science Research Centre at HT, will assess the model’s potential to inform more personalised approaches to prevention.
Alongside validation using existing health records, a clinical pilot conducted with Policlinico Gemelli in Rome will explore how the model’s predictions could support cardiovascular prevention in practice. Working with clinicians, the team will assess how information on possible future disease trajectories can be presented, understood and used within clinical workflows. This will help establish whether these outputs provide useful information beyond conventional risk estimates and identify priorities for further development.
This contribution builds directly on HT’s Cardiovascular & Metabolic Diseases Flagship Research Programme, which includes work to develop generative AI approaches to model cardiometabolic disease progression and trajectories. CHAIN will extend this research into a European validation effort, helping establish how the model performs across different populations and healthcare settings and what would be needed for its future use in clinical practice.
“Predicting cardiovascular risk is an important step towards tailoring prevention to each person’s needs. Through CHAIN, we will test whether the generative AI approaches developed within our Cardiometabolic Flagship Research Programme can provide useful and reliable information across different healthcare settings,” says Emanuele Di Angelantonio. “Working alongside clinical and research partners across Europe will help us understand where these models can add value and what evidence is needed before they can support decisions in everyday care.”
CHAIN will connect hospitals, health data hubs and disease registries through a federated ecosystem aligned with the European Health Data Space, allowing collaboration while keeping personal health data under local control. Evaluation will consider clinical usefulness, fairness, explainability and integration into healthcare workflows, alongside technical performance.
By connecting HT’s research on disease trajectories with European expertise in clinical validation and implementation, CHAIN offers an opportunity to advance the evidence needed for more personalised cardiovascular prevention.
Find out more on the CHAIN website.
The CHAIN project is co-funded by the European Union’s EU4Health Programme under Grant Agreement No. 101314833. The views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Health and Digital Executive Agency (HaDEA). Neither the European Union nor the granting authority can be held responsible for them.
