Possibilities of using Neural Networks to Blood Flow Modelling

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.