Digital twins of the heart are transforming cardiovascular research and clinical decision-making by enabling patient-specific simulations of cardiac function. These advanced computational models require efficient, scalable, and validated software solutions to integrate multimodal data, simulate electrophysiological behaviour, and predict treatment outcomes. Open-source tools play a critical role in this ecosystem, fostering collaboration, transparency, and accessibility in the development of digital twin technologies.
This special session will bring together leading experts in computational cardiology to present state-of-the-art open software solutions for cardiac digital twins. The speakers will showcase innovative methodologies for constructing anatomically detailed models, integrating electrophysiological data from clinical imaging and electroanatomic mapping, and optimizing computational performance using GPU acceleration. Discussions will cover key aspects such as model personalization, AI-driven parameter estimation, and validation strategies to bridge the gap between simulations and clinical applications.
By highlighting cutting-edge open-source frameworks, this session aims to advance the field of computational cardiology and provide researchers and clinicians with the necessary tools to accelerate digital twin adoption in healthcare.