Deep learning for computational hemodynamics: A brief review of recent advances
A Taebi - Fluids, 2022 - mdpi.com
Computational fluid dynamics (CFD) modeling of blood flow plays an important role in better
understanding various medical conditions, designing more effective drug delivery systems …
understanding various medical conditions, designing more effective drug delivery systems …
[HTML][HTML] Beyond CFD: Emerging methodologies for predictive simulation in cardiovascular health and disease
Physics-based computational models of the cardiovascular system are increasingly used to
simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and …
simulate hemodynamics, tissue mechanics, and physiology in evolving healthy and …
Learning reduced-order models for cardiovascular simulations with graph neural networks
L Pegolotti, MR Pfaller, NL Rubio, K Ding… - Computers in Biology …, 2024 - Elsevier
Reduced-order models based on physics are a popular choice in cardiovascular modeling
due to their efficiency, but they may experience loss in accuracy when working with …
due to their efficiency, but they may experience loss in accuracy when working with …
[HTML][HTML] Deep learning-based surrogate model for three-dimensional patient-specific computational fluid dynamics
Optimization and uncertainty quantification have been playing an increasingly important role
in computational hemodynamics. However, existing methods based on principled modeling …
in computational hemodynamics. However, existing methods based on principled modeling …
Physics-constrained coupled neural differential equations for one dimensional blood flow modeling
Background: Computational cardiovascular flow modeling plays a crucial role in
understanding blood flow dynamics. While 3D models provide acute details, they are …
understanding blood flow dynamics. While 3D models provide acute details, they are …
Improved multifidelity Monte Carlo estimators based on normalizing flows and dimensionality reduction techniques
We study the problem of multifidelity uncertainty propagation for computationally expensive
models. In particular, we consider the general setting where the high-fidelity and low-fidelity …
models. In particular, we consider the general setting where the high-fidelity and low-fidelity …
Influence of abdominal aortic aneurysm shape on hemodynamics in human aortofemoral arteries: A transient open-loop study
New imaging methods have enabled the detection of unruptured abdominal aortic
aneurysms (AAA). It is necessary to develop appropriate mathematical models for rupture …
aneurysms (AAA). It is necessary to develop appropriate mathematical models for rupture …
Global sensitivity analysis with multifidelity Monte Carlo and polynomial chaos expansion for vascular haemodynamics
F Schäfer, DE Schiavazzi, LR Hellevik… - … Journal for Numerical …, 2024 - Wiley Online Library
Computational models of the cardiovascular system are increasingly used for the diagnosis,
treatment, and prevention of cardiovascular disease. Before being used for translational …
treatment, and prevention of cardiovascular disease. Before being used for translational …
An augmented streamline upwind/Petrov-Galerkin method for the time-spectral convection-diffusion equation
Discretizing a solution in the spectral rather than time domain presents a significant
advantage in solving transport problems encountered in fields like cardiorespiratory …
advantage in solving transport problems encountered in fields like cardiorespiratory …
Blood flow modeling reveals improved collateral artery performance during the regenerative period in mammalian hearts
S Anbazhakan, PE Rios Coronado… - Nature cardiovascular …, 2022 - nature.com
Collateral arteries bridge opposing artery branches, forming a natural bypass that can
deliver blood flow downstream of an occlusion. Inducing coronary collateral arteries could …
deliver blood flow downstream of an occlusion. Inducing coronary collateral arteries could …