Towards a Digital Twin of the Cardiovascular System

As medicine aims to become smarter, more pervasive, and more personalised, the concept of the Digital Twin has become a cornerstone of the entire base and applied research. The advantages of having Digital Twins to understand, predict and communicate complex mechanisms and functionalities have become of paramount importance in modern and future medicine. This paper presents an approach for the construction of a Digital Twin for the cardiovascular system. The approach, with the objective of being as lightweight and explainable as possible, is based on the integration of partial differential equation models and of realistic data. This integration can overcome both the rigidity of traditional model-based methods and the computational demands of modern deep learning approaches. A technical integration of a smart backend with a frontend based on virtual reality visor is presented in the paper.