Predicting the continuous values of breast cancer relapse time by type-2 fuzzy logic system

  title={Predicting the continuous values of breast cancer relapse time by type-2 fuzzy logic system},
  author={Hamid Mahmoodian},
  journal={Australasian Physical & Engineering Sciences in Medicine},
Microarray analysis and gene expression profile have been widely used in tumor classification, survival analysis and ER statues of breast cancer. Sample discrimination as well as identification of significant genes have been the focus of most previous studies. The aim of this research is to propose a fuzzy model to predict the relapse time of breast cancer by using breast cancer dataset published by van’t Veer. Fuzzy rule mining based on support vector machine has been used in a hybrid method… CONTINUE READING


Publications citing this paper.
Showing 1-2 of 2 extracted citations

Type 2 Fuzzy Logic for mammogram breast tissue classification

2016 International Conference on Industrial Informatics and Computer Systems (CIICS) • 2016
View 5 Excerpts
Highly Influenced


Publications referenced by this paper.
Showing 1-10 of 32 references

Extraction of Fuzzy Rules by Using Support Vector Machines

2008 Fifth International Conference on Fuzzy Systems and Knowledge Discovery • 2008
View 2 Excerpts

Rule extraction using Support Vector Machine based hybrid classifier

TENCON 2008 - 2008 IEEE Region 10 Conference • 2008
View 2 Excerpts

Type-2 Fuzzy Logic: Theory and Applications

Studies in Fuzziness and Soft Computing • 2008
View 1 Excerpt

Type-2 fuzzy sets and systems: an overview

IEEE Computational Intelligence Magazine • 2007
View 1 Excerpt

Similar Papers

Loading similar papers…