Classification of Parkinson's Disease (PD) Based on Multilayer Perception (MLPs) Neural Network and Anova as a feature extraction / Zahari Abu Bakar ... [et al.]

Abu Bakar, Zahari and Ibrahim, Nur Farahiah and Ispawi, Dzufi Iszura and Md. Tahir, Nooritawati (2012) Classification of Parkinson's Disease (PD) Based on Multilayer Perception (MLPs) Neural Network and Anova as a feature extraction / Zahari Abu Bakar ... [et al.]. Masters thesis, Universiti Teknologi MARA, Cawangan Sarawak.

Abstract

Parkinson's disease (PI)) is the second commonest late life neurodegenerative disease after Alzheimer's disease. It is prevalent throughout the world and predominantly affects patients above 60 years old. It is caused by progressive degeneration of dopamine containing cells (neurons) within the deep structures of the brain called the basal ganglia and substantia nigra. Therefore, accurate prediction of PD need to be done in order to assist medical or bio-informatics practitioners for initial diagnose of PD based on variety of test results. This paper described the analysis conducted based on two training algorithms namely Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG) of Multilayer Perceptrons (MLPs) Neural Network in diagnosing PD with Analysis of Variance (ANOVA) as a feature selection. The dataset information of this project has been taken from the Parkinson Disease Data Set. Results attained confirmed that the LM performed well with accuracy rate of above 90% before and after feature selection whilst SSG attained above 85% subsequent to implementation of ANOVA as feature selection.

Metadata

Item Type: Thesis (Masters)
Creators:
Creators
Email / ID Num.
Abu Bakar, Zahari
UNSPECIFIED
Ibrahim, Nur Farahiah
UNSPECIFIED
Ispawi, Dzufi Iszura
UNSPECIFIED
Md. Tahir, Nooritawati
UNSPECIFIED
Subjects: R Medicine > RZ Other systems of medicine
Divisions: Universiti Teknologi MARA, Sarawak > Kota Samarahan Campus > Faculty of Electrical Engineering
Programme: Master in Electrical Engineering
Keywords: Parkinson's Disease, Neurodegenerative Disease
Date: December 2012
URI: https://ir.uitm.edu.my/id/eprint/41423
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