A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

L Liang, W Mao, W Sun - Journal of biomechanics, 2020 - Elsevier
Numerical analysis methods including finite element analysis (FEA), computational fluid
dynamics (CFD), and fluid–structure interaction (FSI) analysis have been used to study the …
被引用次数：90 相关文章

[引用][C] A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

L Liang, W Mao, W Sun - Journal of Biomechanics, 2020 - cir.nii.ac.jp

A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta.

L Liang, W Mao, W Sun - Journal of Biomechanics, 2019 - europepmc.org
Numerical analysis methods including finite element analysis (FEA), computational fluid
dynamics (CFD), and fluid-structure interaction (FSI) analysis have been used to study the …
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[PDF][PDF] A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

L Liang, W Mao, W Sun - Journal of biomechanics, 2020 - drive.google.com
Numerical analysis methods including finite element analysis (FEA), computational fluid 23
dynamics (CFD), and fluid-structure interaction (FSI) analysis have been used to study the …

A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

L Liang, W Mao, W Sun - Journal of biomechanics, 2020 - pubmed.ncbi.nlm.nih.gov
Numerical analysis methods including finite element analysis (FEA), computational fluid
dynamics (CFD), and fluid-structure interaction (FSI) analysis have been used to study the …

A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta

L Liang, W Mao, W Sun - Journal of biomechanics, 2020 - scholarship.miami.edu
Numerical analysis methods including finite element analysis (FEA), computational fluid
dynamics (CFD), and fluid–structure interaction (FSI) analysis have been used to study the …