Data-Mining models for the Diagnosis of EMG-based Neuromuscular Diseases
by Babita Pandey, R.B. Mishra
International Journal of Biomedical Engineering and Technology (IJBET), Vol. 6, No. 2, 2011

Abstract: Data-Mining (DM) methods such as Decision Tree (DT), Artificial Neural Network (ANN) and Sensitivity Analysis (SA) have been extensively used in the medical and biomedical domains but these methods and their combinations have been rarely used in the diagnosis of Neuromuscular Diseases (NMDs). In this paper, we use various methods of DM such as: DT, ANN and SA and their combination. A comparative study is made on these combined methods to determine the methods with highest degree of accuracy. The results show that in combined SA–ANN models SA–ANN (RBFN) has highest accuracy. In SA–DT model and DT–ANN model, all the three methods, i.e., quick, dynamic and RBFN have equal accuracy.

Online publication date: Wed, 21-Jan-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biomedical Engineering and Technology (IJBET):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com