Diagnosing Parkinson by using Artificial Neural Networks and Support Vector Machines

Global Journal of Computer Science and Technology, Vol 9, No 4 (2009)

Diagnosing Parkinson by using Artificial Neural Networks and Support Vector Machines

David Gil, Devadoss Johnson Manuel

Abstract

Parkinson\'s Disease (PD) is the second most common neurodegenerative aï¿½iction only surpassed by Alzheimer\'s Disease (AD). Moreover, it is expected to increase in the next decade with accelerating treatment costs as a consequence. This situation leads us towards the need to develop a Decision Support System for PD. In this paper we propose methods based on ANNs and SVMs to aid the specialist in the diagnosis of PD. Data recorded during 195 examinations carried out on 31 patients was used to verify the capacity of the proposed system. The results show a high accuracy of around 90%.

Full Text: PDF

This work is licensed under a Creative Commons Attribution 3.0 License.

Copyright © 2001-2010 by Global Journals Inc. (US) – All Rights ReservedThe use of this site, and the terms and conditions for our providing information, is governed by our Disclaimer, Terms and Conditions and Privacy Policy.By using this site, this signifies and you acknowledge that you have read them and that you accept and will be bound by the terms thereof.All information, activities undertaken, materials, services and this website is subject to change anytime without any prior notice.

Best Viewed on FireFox Browsers with Flash Player and Resolution more than or equals 1024x768

USA Incorporation No.: 0423089 | USA Tax ID (Employer ID No.): 098-0673227 | License No.: 42125/022010/1186 | Registration No.: 430374 | Import-Export Code: 1109007027