A deep learning approach to estimate stress distribution: a fast and accurate surrogate of finite-element analysis
Structural finite-element analysis (FEA) has been widely used to study the biomechanics of
human tissues and organs, as well as tissue–medical device interactions, and treatment …
human tissues and organs, as well as tissue–medical device interactions, and treatment …
A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta
Numerical analysis methods including finite element analysis (FEA), computational fluid
dynamics (CFD), and fluid–structure interaction (FSI) analysis have been used to study the …
dynamics (CFD), and fluid–structure interaction (FSI) analysis have been used to study the …
[HTML][HTML] A deep learning framework for design and analysis of surgical bioprosthetic heart valves
A Balu, S Nallagonda, F Xu, A Krishnamurthy… - Scientific reports, 2019 - nature.com
Bioprosthetic heart valves (BHVs) are commonly used as heart valve replacements but they
are prone to fatigue failure; estimating their remaining life directly from medical images is …
are prone to fatigue failure; estimating their remaining life directly from medical images is …
Bridging finite element and machine learning modeling: stress prediction of arterial walls in atherosclerosis
Finite element and machine learning modeling are two predictive paradigms that have rarely
been bridged. In this study, we develop a parametric model to generate arterial geometries …
been bridged. In this study, we develop a parametric model to generate arterial geometries …
Simulating progressive intramural damage leading to aortic dissection using DeepONet: an operator–regression neural network
Aortic dissection progresses mainly via delamination of the medial layer of the wall.
Notwithstanding the complexity of this process, insight has been gleaned by studying in vitro …
Notwithstanding the complexity of this process, insight has been gleaned by studying in vitro …
A machine learning approach to investigate the relationship between shape features and numerically predicted risk of ascending aortic aneurysm
Geometric features of the aorta are linked to patient risk of rupture in the clinical decision to
electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused …
electively repair an ascending aortic aneurysm (AsAA). Previous approaches have focused …
[HTML][HTML] A deep learning approach to predict abdominal aortic aneurysm expansion using longitudinal data
An abdominal aortic aneurysm (AAA) is a gradual enlargement of the aorta that can cause a
life-threatening event when a rupture occurs. Aneurysmal geometry has been proved to be a …
life-threatening event when a rupture occurs. Aneurysmal geometry has been proved to be a …
Predictive constitutive modelling of arteries by deep learning
GA Holzapfel, K Linka… - Journal of the Royal …, 2021 - royalsocietypublishing.org
The constitutive modelling of soft biological tissues has rapidly gained attention over the last
20 years. Current constitutive models can describe the mechanical properties of arterial …
20 years. Current constitutive models can describe the mechanical properties of arterial …
A generic physics-informed neural network-based constitutive model for soft biological tissues
Constitutive modeling is a cornerstone for stress analysis of mechanical behaviors of
biological soft tissues. Recently, it has been shown that machine learning (ML) techniques …
biological soft tissues. Recently, it has been shown that machine learning (ML) techniques …
Neural operator learning of heterogeneous mechanobiological insults contributing to aortic aneurysms
Thoracic aortic aneurysm (TAA) is a localized dilatation of the aorta that can lead to life-
threatening dissection or rupture. In vivo assessments of TAA progression are largely limited …
threatening dissection or rupture. In vivo assessments of TAA progression are largely limited …