About the paper
Title |
Prediction of wall shear stress in the arteries with myocardial bridge by neural networks |
Book |
ICIST 2015 Proceedings |
Pages |
219-222 |
Abstract: Coronary arteries and their major branches,
which supply oxygenated and nutrient filled blood to the
heart muscle (myocardium), lie on the surface of the heart,
in the subepicardial space, between visceral pericardium
(epicardium) and myocardium. Sometimes, a shorter or
longer segment of the epicardial coronary artery or its
branch is covered by a band of heart muscle that lies on top
of it. This band of muscle is called a “bridge” and the
intramural segment of coronary artery a “tunneled artery”.
Myocardial bridging (MB) is a congenital coronary anomaly
defined as a segment of a major epicardial coronary artery
that runs intramurally through the myocardium beneath
the muscle bridge.
It is very important to find the most efficient method for
determining shear stress in the coronary arteries with
myocardial bridge.
The procedure for calculating shear stress in MB arteries
using neural networks trained with results from finite
elements method will be explained in this paper. |
Full citation
Nikolić, D.,
Saveljić, I.,
Radović, M.,
Aleksandrić, S.,
Tomašević, M.,
Ranković, V.,
Filipović, N.
Prediction of wall shear stress in the arteries with myocardial bridge by neural networks. In:
Zdravković, M.,
Trajanović, M.,
Konjović, Z.
(Eds.)
ICIST 2015 Proceedings, pp.219-222, 2015
Keywords
Healthcare and medicine
Neural networks
Machine learning
Finite Element Analysis