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Author(s): Carlos C. António
Catarina F. Castro
Luísa C. Sousa
Rui Chaves
Title: Predictions of blood flow varations based on artificial neural network and doppler signal
Issue Date: 2012
Abstract: In this approach a surrogate model based on Artificial Neural Networks (ANN), Doppler signal and Finite Element Method (FEM) is developed aiming to investigate the carotid arterial conditions. Doppler measurements of blood flow velocities are used as input values in Artificial Neural Network developments based on supervised learning. The network is trained using a Genetic Algorithm (GA) supported by an elitist strategy to obtain the optimal ANN topology. The ANN is cross validated and tested with carotid arterial Doppler signal and FEM analysis. The use of this ANN surrogate model for classification of carotid arterial diagnosis problems is proposed.
Subject: Ciências Tecnológicas, Ciências da Saúde, Outras ciências da engenharia e tecnologias
Technological sciences, Health sciences, Other engineering and technologies
Scientific areas: Ciências da engenharia e tecnologias::Outras ciências da engenharia e tecnologias
Engineering and technology::Other engineering and technologies
Source: Proceedings ICEM15 - 15th International Conference on Experimental Mechanics
Document Type: Artigo em Livro de Atas de Conferência Internacional
Rights: restrictedAccess
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

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