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Article:Parkinson Disease Classification using Data Mining Algorithms

by Dr. R. Geetha Ramani, G. Sivagami
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 32 - Number 9
Year of Publication: 2011
Authors: Dr. R. Geetha Ramani, G. Sivagami
10.5120/3932-5571

Dr. R. Geetha Ramani, G. Sivagami . Article:Parkinson Disease Classification using Data Mining Algorithms. International Journal of Computer Applications. 32, 9 ( October 2011), 17-22. DOI=10.5120/3932-5571

@article{ 10.5120/3932-5571,
author = { Dr. R. Geetha Ramani, G. Sivagami },
title = { Article:Parkinson Disease Classification using Data Mining Algorithms },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 32 },
number = { 9 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 17-22 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume32/number9/3932-5571/ },
doi = { 10.5120/3932-5571 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:18:44.809475+05:30
%A Dr. R. Geetha Ramani
%A G. Sivagami
%T Article:Parkinson Disease Classification using Data Mining Algorithms
%J International Journal of Computer Applications
%@ 0975-8887
%V 32
%N 9
%P 17-22
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Knowledge discovery in databases has established its success rate in various prominent fields such as e-business, marketing, retail and medical. Medical data mining has great potency for exploring the out of sight patterns in the respective medical data sets. This paper intends to provide a survey of current techniques of knowledge discovery in databases using data mining techniques that are in use today for the classification of Parkinson Disease. Parkinson Disease is a chronic malady of the central nervous system where the key indications can be captivated from the Mentation, Activities of Daily Life (ADL), Motor Examination and Complications of Therapy. The speech symptom which is an ADL is a common ground for the progress of the disease. The dataset for the disease is acquired from UCI, an online repository of large data sets. A comparative study on different classification methods is carried out to this dataset by applying the feature relevance analysis and the Accuracy Analysis to come up with the best classification rule. Also the intention is to sieve the data such that the healthy and people with Parkinson will be correctly classified.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Knowledge Data Discovery (KDD) Data Mining Error Rate Classification mis-Classification Rate Feature Relevance Clinical Data Parkinson Disease