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Iris disease classifying using neuro-fuzzy medical diagnosis machine

Moein, S, Saraee, M and Moein, M 2009, 'Iris disease classifying using neuro-fuzzy medical diagnosis machine' , in: The Sixth International Symposium on Neural Networks (ISNN 2009) , Springer Berlin / Heidelberg, , pp. 359-368.

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Abstract

Disease diagnosis is an essential task in the medical world. The use of computers in the practice of medicine is becoming more and more crucial. In this paper, we propose an intelligent system to help us diagnose the Iris disease. This system is based on Artificial Neural Network (ANN) approach. In order to evaluate our proposed approach we apply the system on a dataset which includes all related symptoms. Next multilayer perceptron ANN is trained to be able to classify. In order to obtain the best results we use different measure values. Finally data fuzzification is employed to improve the stem performance.

Item Type: Book Section
Themes: Health and Wellbeing
Schools: Colleges and Schools > College of Science & Technology > School of Computing, Science and Engineering > Data Mining and Pattern Recognition Research Centre
Publisher: Springer Berlin / Heidelberg,
Refereed: Yes
ISBN: 978-3-642-01215-0
ISSN: 1867-5662
Depositing User: Dr Mo Saraee
Date Deposited: 21 Oct 2011 11:48
Last Modified: 20 Aug 2013 18:15
URI: http://usir.salford.ac.uk/id/eprint/18588

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