Fuzzy Classifier for the Diagnosis of Pathology on the Vertebral Column

Author

Contreras, Javier ; Bonfante, Maria Claudia ; Quintana, Alvaro ; Castro, Veronica

Author_Institution

Escuela Naval Almirante Padilla, Corp. Univ. Rafael Nunez, Cartagena, Colombia

Volume

12

Issue

6

fYear

2014

fDate

Sept. 2014

Firstpage

1149

Lastpage

1154

Abstract

This paper describes the training and application of a fuzzy singleton classifier that is used for the diagnosis of pathologies of the vertebral column, discriminating patients as belonging to one out of three categories: Normal, Disk Hernia and Spondylolisthesis. Each input variable is partitioned into triangular membership functions so that consecutive fuzzy sets exhibit and specific overlapping of 0.5. Singleton consequents are employed and least square method is used to adjust the consequents. Applications are conducted on the vertebral column data set from University of California Irvine UCI Machine Learning Repository. Features of the dataset are obtained from sagittal panoramic radiographies of the spine. The dataset includes 310 instances (310 patients) having 6 real valued attributes in 3 classes

Keywords

biology computing; fuzzy set theory; pattern classification; UCI machine learning repository; consecutive fuzzy sets; disk hernia; fuzzy singleton classifier; least square method; pathology; patients; sagittal panoramic radiographies; spine; spondylolisthesis; triangular membership functions; vertebral column data set; Biological system modeling; IP networks; Muscles; Pathology; Pelvis; Support vector machines; Vectors; diagnosis; disk hernia; fuzzy classifier; spondylolisthesis; vertebral column;

fLanguage

English

Journal_Title

Latin America Transactions, IEEE (Revista IEEE America Latina)

Publisher

ieee

ISSN

1548-0992

Type

jour

DOI

10.1109/TLA.2014.6894013

Filename

6894013