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Mass spectrometry-based proteomic data for cancer diagnosis using interval type-2 fuzzy system

conference contribution
posted on 2015-01-01, 00:00 authored by Thanh Thi NguyenThanh Thi Nguyen, Saeid Nahavandi, Abbas KhosraviAbbas Khosravi, Douglas CreightonDouglas Creighton
An interval type-2 fuzzy logic system is introduced for cancer diagnosis using mass spectrometry-based proteomic data. The fuzzy system is incorporated with a feature extraction procedure that combines wavelet transform and Wilcoxon ranking test. The proposed feature extraction generates feature sets that serve as inputs to the type-2 fuzzy classifier. Uncertainty, noise and outliers that are common in the proteomic data motivate the use of type-2 fuzzy system. Tabu search is applied for structure learning of the fuzzy classifier. Experiments are performed using two benchmark proteomic datasets for the prediction of ovarian and pancreatic cancer. The dominance of the suggested feature extraction as well as type-2 fuzzy classifier against their competing methods is showcased through experimental results. The proposed approach therefore is helpful to clinicians and practitioners as it can be implemented as a medical decision support system in practice.

History

Event

IEEE International Conference on Fuzzy Systems (2015 : Istanbul, Turkey)

Series

IEEE International Fuzzy Systems Conference Proceedings

Pagination

1 - 8

Publisher

IEEE

Location

Istanbul, Turkey

Place of publication

Piscataway, N.J.

Start date

2015-08-02

End date

2015-08-05

ISSN

1544-5615

ISBN-13

9781467374286

Language

eng

Publication classification

E Conference publication; E1 Full written paper - refereed

Copyright notice

2015, IEEE

Editor/Contributor(s)

A Yazici, N Pal, U Kaymak, T Martin, H Ishibuchi, C Lin, J Sousa, B Tutmez

Title of proceedings

UZZ-IEEE 2015: Proceedings of the IEEE International Conference on Fuzzy Systems