… We evaluated the feasibility of optimising coronary perfusion pressure (CPP) during … This
study shows that machine learning algorithms can be deployed successfully to predict CPR …

… residual learning scheme to make it computationally feasible. A … the subsequent calculation
of hemodynamic quantities. … rely on residual learning, where we predict the fine detail using a …

… : predictive simulation of the effects of endovascular stenting in a coarcted descending aorta;
… Eventually, another class of machine learning models that can actually change the rules of …

… To mitigate this challenge, machine learning (ML) models, eg, deep neural networks (DNNs)…
In this study, we adapted this network to predict the displacement field of an aorta from the …

… by CFD simulations in the thoracic aorta and modified to be consistent … , some investigators
have examined the feasibility and … The prediction of other hemodynamic parameters was less …

… to reduce the cost of UQ to a feasible scale. The first strategy involves … predicts hemodynamic
quantities averaged over a cardiac cycle duration and limits the outputs to be predicted…

… diseases, deep learning-based predictive models have … Repair (TEVAR) require preoperative
feasibility assessment … in the local correlations between hemodynamic indices, biological …

… A feasibility study of deep learning for predicting hemodynamics of human thoracic aorta. J
… CFD to estimate steady-state hemodynamic fields of human thoracic aorta. In their approach, …

… the feasibility of employing PINNs to inform hemodynamics … Next, we examine the predictions
of the flow field in the other … from data science and machine learning domain experts, while …

… predict haemodynamics in large vascular networks and over a long time. Here we investigate
the applicability of machine learning (ML) techniques to predict … ML models predict the time-…