Referenced Items are not available for this document.
A novel convex set based neuro-fuzzy algorithm for classification of difficult-to-diagnose instances of breast cancer is described. The new approach offers rational advantages over the leading neural algorithm backpropagation. The comparative results obtained using receiver operating characteristic (ROC) analysis show that the ability of the convex set based method to infer knowledge is better than that of backpropagation, making it more suitable for use in real diagnostic systems
Published in:
[Engineering in Medicine and Biology, 1999. 21st Annual Conference and the 1999 Annual Fall Meetring of the Biomedical Engineering Society] BMES/EMBS Conference, 1999. Proceedings of the First Joint
(Volume:2
)
Date of Conference: Oct 1999
- Meeting Date :
- 13 Oct 1999-16 Oct 1999
- ISSN :
- 1094-687X
- Print ISBN:
- 0-7803-5674-8
- INSPEC Accession Number:
- 6513374
- Conference Location :
- Atlanta, GA
- Digital Object Identifier :
- 10.1109/IEMBS.1999.804296
- Product Type:
- Conference Publications
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 2013 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
