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Towards High-Fidelity and Efficient Computation for Diagnosis and Treatment of Cardiovascular Disease

Lei Wang^1,*, Blanca Rodriguez², Xiaoyu Luo³, Charles Augarde⁴

1 Beijing National Center for Applied Mathematics, Academy for Multidisciplinary Studies, Capital Normal University, 105 West Third Ring Road North, Haidian District, Beijing, 100048, China
2 Department of Computer Science, University of Oxford, 7 Parks Rd, Oxford, OX1 3QG, UK
3 School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8QW, UK
4 Department of Engineering, Durham University, South Rd, Durham, DH1 3LE, Durham, UK

* Corresponding Author: Lei Wang. Email:

The International Conference on Computational & Experimental Engineering and Sciences 2024, 30(4), 1-2. https://doi.org/10.32604/icces.2024.013350

Abstract

Cardiovascular disease is the leading cause of death worldwide. Disease-specific software, like FFRct from HeartFlow, and high-fidelity computational models within a general-purpose software, like Living Heart Project within Abaqus, are essential to revolutionise diagnosis and treatment of cardiovascular disease for clinicians and design of medical devices for industries. This talk presents our past researches on computational modelling of tear propagation in the aortic dissection [1-2] and of electromechanical coupling in the human heart with the finite element method [3], and our current exploration on high-fidelity and efficient computation and software development for diagnosis and treatment of cardiovascular disease with advanced computational methods [4-5] and models.

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Keywords

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