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Cardiovascular diseases identified at an early stage using machine learning and digital twins, eliminating the need for expensive diagnostic methods like MRI or CT
How can diseases of the cardiovascular system be detected before symptoms appear? Researchers at Graz University of Technology (TU Graz) have found a way to track them down at an early stage.
During their doctoral theses as part of the TU Graz lead project “ Mechanics, Modelling and Simulation of Aortic Dissection ” led by Gerhard Holzapfel, Sascha Ranftl from the Institute of Theoretical and Computational Physics and Vahid Badeli from the Institute of Fundamentals and Theory in Electrical Engineering at TU Graz found a way to improve and accelerate the early detection of such diseases without the use of expensive diagnostic methods such as MRI or CT. In the TU Graz spin-off arterioscope, Sascha Ranftl and Vahid Badeli are now developing this technology further together with partners from the healthcare sector in order to enhance the accuracy of their current algorithms and further extend and adapt them for clinical practice. The starting point for this development was the interdisciplinary work with their colleagues in the lead project and the fact that their two specialisms complement each other perfectly: Sascha Ranftl is a physicist and Vahid Badeli is an electrical engineer.
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