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Computational and Mathematical Methods in Medicine
Volume 2014 (2014), Article ID 985789, 14 pages
http://dx.doi.org/10.1155/2014/985789
Research Article

An Efficient Diagnosis System for Parkinson’s Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach

1College of Computer Science and Technology, Jilin University, No. 2699, QianJin Road, Changchun 130012, China
2Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China
3College of Physics and Electronic Information, Wenzhou University, Wenzhou 325035, China

Received 21 June 2014; Accepted 26 October 2014; Published 18 November 2014

Academic Editor: Dong Song

Copyright © 2014 Chao Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Chao Ma, Jihong Ouyang, Hui-Ling Chen, and Xue-Hua Zhao, “An Efficient Diagnosis System for Parkinson’s Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach,” Computational and Mathematical Methods in Medicine, vol. 2014, Article ID 985789, 14 pages, 2014. doi:10.1155/2014/985789