Title: Diagnosis of EEG-based diseases using data mining and case-based reasoning

Authors: Babita Pandey; Depika Kundra

Addresses: School of Computer Application, Lovely Professional University, Phagwara, Panjab, India ' School of Computer Application, Lovely Professional University, Phagwara, Panjab, India

Abstract: Medical diagnosis system (MDS) provides facility to clinical experts for diagnosis of the different diseases. This paper focus on the development of the MDS for the diagnosis of electroencephalography (EEG)-based diseases, integrating J48 (data mining) and case-based reasoning (CBR). These integrated systems reduce the error amount and degree of uncertainty. Brain is the bioelectric generator. Neurological disordering in the brain leads some problems like muscle weakness and abnormal brain functioning. EEG is a medical imaging techniques that helps to measure the abnormality occurs in the electric activity of the human brain. It gives the information about the level of consciousness of the person, and also contains very useful information relating to different physiological state of brain. In this work, firstly, J48 algorithm is used for reducing the dimension of parameters. After that CBR is implemented for diagnosis of the different EEG-based diseases. The integration of J48 and CBR improves the accuracy of diagnosis and solve the problem of knowledge acquisition.

Keywords: EEG signals; disease diagnosis; data mining; J48 algorithm; case-based reasoning; CBR; medical diagnosis; electroencephalograms; medical images; knowledge acquisition; neurological disorders.

DOI: 10.1504/IJISDC.2017.082851

International Journal of Intelligent Systems Design and Computing, 2017 Vol.1 No.1/2, pp.43 - 55

Received: 08 May 2014
Accepted: 14 Dec 2014

Published online: 10 Mar 2017 *

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