DocumentCode :
3698243
Title :
Mass spectrometry-based proteomic data for cancer diagnosis using interval type-2 fuzzy system
Author :
Thanh Nguyen;Saeid Nahavandi;Abbas Khosravi;Douglas Creighton
Author_Institution :
Centre for Intelligent Systems Research (CISR), Deakin University, Victoria, 3216, Australia
fYear :
2015
Firstpage :
1
Lastpage :
8
Abstract :
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.
Keywords :
"Cancer","Feature extraction","Fuzzy logic","Frequency selective surfaces","Proteomics","Uncertainty","Wavelet coefficients"
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ-IEEE), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/FUZZ-IEEE.2015.7338078
Filename :
7338078
Link To Document :
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