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Using support vector regression in gene selection and fuzzy rule generation for relapse time prediction of breast cancer

Paper ID Volume ID Publish Year Pages File Format Full-Text
5134 342 2016 7 PDF Available
Title
Using support vector regression in gene selection and fuzzy rule generation for relapse time prediction of breast cancer
Abstract

Gene expression profiles have been recently used in survival analysis, tumor classification and ER status identification. The prediction of breast cancer recurrence based on gene expression profile has been regarded in some previous studies in which the procedures were based on the concept of regression functions and fuzzy systems. In this study, a method based on the combination of these two concepts is presented; not only a method for gene selection, but also a systematic way to create fuzzy rules are going to be offered. Due to the ability of type-2 fuzzy systems in handling of uncertain systems, the proposed model is developed to type-2. The results show that this model has been improved in comparison to previous ones.

Keywords
Support vector regression; Type 2 fuzzy logic; Relapse time
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Using support vector regression in gene selection and fuzzy rule generation for relapse time prediction of breast cancer
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Publisher
Database: Elsevier - ScienceDirect
Journal: Biocybernetics and Biomedical Engineering - Volume 36, Issue 3, 2016, Pages 466–472
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us