Cart (Loading....) | Create Account
Close category search window
 

Comparison of four computer-aided diagnosis schemes for automated discrimination of myocardial heart disease

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Du-Yih Tsai ; Dept. of Radiol. Technol., Niigata Univ., Japan

The aim of this paper is to compare the performance of four different methods, i.e., neural network (NN) with backpropagation learning, NN with genetic-algorithm-based (GA-based) learning, fuzzy reasoning, and the GA-based fuzzy logic approach, for automated discrimination of myocardial heart disease. In our experiments, a total of 90 samples of echocardiographic images from 45 subjects were used. Our results showed that the GA-based fuzzy logic approach is superior to the other three methods. This method enables the classification to achieve a 95.9% of accuracy

Published in:

Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on  (Volume:3 )

Date of Conference:

2000

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.