Possibilities of using Neural Networks to Blood Flow Modelling

Katarína Buzáková, Katarína Bachratá, Hynek Bachratý, Michal Chovanec

2021

Abstract

Computer simulation of the flow of blood or other fluid is beneficial to reduce the variety of costs necessary for biological experiments in microfluidics. It turns out, that as biological experiments, even the simulations have limitations. However, data from both types of experiments can be further processed by machine learning methods in order to improve them and thus contribute to the optimization of microfluidic devices. This article describes the possibilities of using neural networks to blood flow modelling. In this paper, we focus mainly on the prediction of red blood cells movement. We propose other possibilities of using neural networks with regard to the needs of further research in simulation modelling.

Paper Citation

in Harvard Style

Buzáková K., Bachratá K., Bachratý H. and Chovanec M. (2021). Possibilities of using Neural Networks to Blood Flow Modelling. In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 3: BIOINFORMATICS; ISBN 978-989-758-490-9, SciTePress, pages 140-147. DOI: 10.5220/0010314100002865

in Bibtex Style

@conference{bioinformatics21,
author={Katarína Buzáková and Katarína Bachratá and Hynek Bachratý and Michal Chovanec},
title={Possibilities of using Neural Networks to Blood Flow Modelling},
booktitle={Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 3: BIOINFORMATICS},
year={2021},
pages={140-147},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010314100002865},
isbn={978-989-758-490-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 3: BIOINFORMATICS
TI - Possibilities of using Neural Networks to Blood Flow Modelling
SN - 978-989-758-490-9
AU - Buzáková K.
AU - Bachratá K.
AU - Bachratý H.
AU - Chovanec M.
PY - 2021
SP - 140
EP - 147
DO - 10.5220/0010314100002865
PB - SciTePress