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Adaptive Neuro-Fuzzy Inference System for Classihcation of Urodynamic Test

by Mohanad A.deaf, Mohamed A.a.eldosoky
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 118 - Number 16
Year of Publication: 2015
Authors: Mohanad A.deaf, Mohamed A.a.eldosoky
10.5120/20832-3500

Mohanad A.deaf, Mohamed A.a.eldosoky . Adaptive Neuro-Fuzzy Inference System for Classihcation of Urodynamic Test. International Journal of Computer Applications. 118, 16 ( May 2015), 31-34. DOI=10.5120/20832-3500

@article{ 10.5120/20832-3500,
author = { Mohanad A.deaf, Mohamed A.a.eldosoky },
title = { Adaptive Neuro-Fuzzy Inference System for Classihcation of Urodynamic Test },
journal = { International Journal of Computer Applications },
issue_date = { May 2015 },
volume = { 118 },
number = { 16 },
month = { May },
year = { 2015 },
issn = { 0975-8887 },
pages = { 31-34 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume118/number16/20832-3500/ },
doi = { 10.5120/20832-3500 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:01:54.909286+05:30
%A Mohanad A.deaf
%A Mohamed A.a.eldosoky
%T Adaptive Neuro-Fuzzy Inference System for Classihcation of Urodynamic Test
%J International Journal of Computer Applications
%@ 0975-8887
%V 118
%N 16
%P 31-34
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Urodynamic test is a method that assesses how the bladder and urethra are performing their functions of storing and releasing of the urine. The aim of this paper is to develop an approach for classifying of Urodynamic result to normal and abnormal value using adaptive neuro fuzzy inference system. The data of Urodynamic were obtained from the Institute of Experimental Clinical Research. Eight Urodynamic Components are used as input for the prediction model. Simulations were run in Matlab. The simulation results demonstrate that the model successfully to classify the Urodynamic Components to normal and abnormal values with an accuracy rate of 97. 30%.

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Index Terms

Computer Science
Information Sciences

Keywords

Adaptive neuro-fuzzy inference system (ANFIS) ANFIS Classifier Urodynamic testing (UDS).

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