Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/11931
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dc.rights.licenserestrictedAccess-
dc.contributor.authorBlagojević, Marija-
dc.contributor.authorRadović M.-
dc.contributor.authorRadović, Maja-
dc.contributor.authorFilipovic, Nenad-
dc.date.accessioned2021-04-20T19:35:34Z-
dc.date.available2021-04-20T19:35:34Z-
dc.date.issued2015-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/11931-
dc.description.abstract© 2015 IEEE. This paper describes the use of artificial neural networks in predicting value and position maximal wall shear stress in aneurysm. For the purpose of neural network training, back propagation algorithm was used. Input data in the network are geometric parameters of aneurysm model. Obtained results indicate the possibility of a successful application of neural networks in the problems of predicting certain parameters of arteries. Future work relates to the creation of a web-based application that allows users to display the results.-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.source2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015-
dc.titleNeural network based approach for predicting maximal wall shear stress in the artery-
dc.typeconferenceObject-
dc.identifier.doi10.1109/BIBE.2015.7367713-
dc.identifier.scopus2-s2.0-84962890423-
Appears in Collections:Faculty of Engineering, Kragujevac
Faculty of Technical Sciences, Čačak

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