Towards fast and reliable estimations of 3D pressure, velocity and wall shear stress in aortic blood flow: CFD-based machine learning approach.
- DOI
- 10.1016/j.compbiomed.2025.110137
- Published
- 2025 Jun
- Container
- Computers in biology and medicine
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.compbiomed.2025.110137,
title = {Towards fast and reliable estimations of 3D pressure, velocity and wall shear stress in aortic blood flow: CFD-based machine learning approach.},
author = {Lin D and Kenjereš S},
year = {2025},
journal = {Computers in biology and medicine},
doi = {10.1016/j.compbiomed.2025.110137},
url = {https://doi.org/10.1016/j.compbiomed.2025.110137}
}RIS
TY - JOUR TI - Towards fast and reliable estimations of 3D pressure, velocity and wall shear stress in aortic blood flow: CFD-based machine learning approach. AU - Lin D AU - Kenjereš S PY - 2025 JO - Computers in biology and medicine DO - 10.1016/j.compbiomed.2025.110137 UR - https://doi.org/10.1016/j.compbiomed.2025.110137 ER -
APA
D, L., & S, K. (2025). Towards fast and reliable estimations of 3D pressure, velocity and wall shear stress in aortic blood flow: CFD-based machine learning approach.. Computers in biology and medicine. https://doi.org/10.1016/j.compbiomed.2025.110137
Source records
- pubmed · retrieved 2026-09-26T04:48:10.773Z