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Comparison of the Data Classification Approaches to Diagnose Spinal Cord Injury
Joint Authors
Karamehmetoglu, Safak Sahir
Arslan, Yunus Ziya
Ugur, Mukden
Palamar, Deniz
Demirer, Rustu Murat
Source
Computational and Mathematical Methods in Medicine
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-03-05
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
In our previous study, we have demonstrated that analyzing the skin impedances measured along the key points of the dermatomes might be a useful supplementary technique to enhance the diagnosis of spinal cord injury (SCI), especially for unconscious and noncooperative patients.
Initially, in order to distinguish between the skin impedances of control group and patients, artificial neural networks (ANNs) were used as the main data classification approach.
However, in the present study, we have proposed two more data classification approaches, that is, support vector machine (SVM) and hierarchical cluster tree analysis (HCTA), which improved the classification rate and also the overall performance.
A comparison of the performance of these three methods in classifying traumatic SCI patients and controls was presented.
The classification results indicated that dendrogram analysis based on HCTA algorithm and SVM achieved higher recognition accuracies compared to ANN.
HCTA and SVM algorithms improved the classification rate and also the overall performance of SCI diagnosis.
American Psychological Association (APA)
Arslan, Yunus Ziya& Demirer, Rustu Murat& Palamar, Deniz& Ugur, Mukden& Karamehmetoglu, Safak Sahir. 2012. Comparison of the Data Classification Approaches to Diagnose Spinal Cord Injury. Computational and Mathematical Methods in Medicine،Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-499347
Modern Language Association (MLA)
Arslan, Yunus Ziya…[et al.]. Comparison of the Data Classification Approaches to Diagnose Spinal Cord Injury. Computational and Mathematical Methods in Medicine No. 2012 (2012), pp.1-7.
https://search.emarefa.net/detail/BIM-499347
American Medical Association (AMA)
Arslan, Yunus Ziya& Demirer, Rustu Murat& Palamar, Deniz& Ugur, Mukden& Karamehmetoglu, Safak Sahir. Comparison of the Data Classification Approaches to Diagnose Spinal Cord Injury. Computational and Mathematical Methods in Medicine. 2012. Vol. 2012, no. 2012, pp.1-7.
https://search.emarefa.net/detail/BIM-499347
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-499347