Harnessing the potential of artificial intelligence applied to cardiology and transforming cardiovascular research through high-fidelity data and personalised digital twins. With this aim, the COR Research Group at the ITACA Institute of the Universitat Politècnica de València launched the HELIOS project (High-Efficiency Library for the Integration and Optimisation of Electrophysiological Simulations) on 1 February.
Funded by the Agencia Estatal de Investigación (MCIN/AEI/10.13039/501100011033, PDC2025-165776-I00), the project will run for two years and is designed to accelerate research, technological development and the transfer of advanced solutions in cardiology.
“The main goal is to improve the diagnosis and treatment of atrial fibrillation, contributing to better health outcomes and more equitable access to advanced cardiac simulation tools”, says María S. Guillem, project coordinator and Director of ITACA.
Coinciding with World Pulse Day on 1 March, held yesterday, the COR Group highlights the importance of heart rhythm and raises awareness of conditions such as atrial fibrillation, which affects more than 66 million people worldwide.
Overcoming the data bottleneck in medical artificial intelligence
The project is based on a widely recognised reality in the field of digital health: the main challenge currently facing medical artificial intelligence lies not in the algorithms, but in the limited availability of accessible, diverse, reproducible clinical data that comply with privacy regulations.
In this context, HELIOS proposes transforming the DYNAMO cardiac simulation engine into a Data-as-a-Service (DaaS) platform capable of generating standardised synthetic cardiac data on demand, ready for use in artificial intelligence algorithms, in silico clinical trials and technology validation processes.
“This platform will make high-fidelity cardiac data available without the ethical, logistical or regulatory limitations associated with the use of real clinical data”, explains María S. Guillem.
Conceived as a genuine “data factory”, HELIOS will enable the creation of patient-specific cardiac digital twins capable of reproducing not only the heart’s anatomy but also its electrical pathophysiology.
In addition, the project will offer distinct added value in three key areas: the training and validation of medical AI algorithms, the creation of virtual patient cohorts for in silico clinical trials, and support for regulatory and certification processes through reproducible performance data.
Technology transfer and patient impact
From a strategic perspective, the project represents a key step forward in the technological maturation of the COR Group, evolving from laboratory-validated technologies to a pre-commercial platform, thereby ensuring effective knowledge transfer to the biomedical industry.
“Our ultimate aim is for these tools to reach clinical practice and help improve the diagnosis and treatment of atrial fibrillation, moving towards truly personalised cardiology”, concludes María S. Guillem.
