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A Comparative Study of Neural Network Techniques to Perform Early Diagnosis of Alzheimer's Disease

Authors:
Lara Dantas
Mêuser Valença

Keywords: Reservoir Computing; Alzheimer’s Disease; Neural Network

Abstract:
The life expectancy of the population in most developed countries is growing every day and hence there is an increase of several age-related diseases. In Brazil, about 1.2 million people have Alzheimer's disease (AD), now considered the most common type of dementia in the population. Although it is a degenerative and irreversible disease, if diagnosed early, medications may be administered to slow the progression of symptoms and provide a better quality of life for the patient. Previous studies with classifiers contained in the software Weka using a database with values of 120 blood proteins, and they noticed that they could classify the patient may or may not be diagnosed with AD with an accuracy rate of 94% and 85%, respectively. Thus, this study aims to use a new connectionist approach called Reservoir Computing (RC) to perform early diagnosis of a patient with or without AD, also compare these results with those obtained using a Neural Network Multi-Layer Perceptron (MLP). This article also envisions to utilize the Random Forest Algorithm to select proteins from the original set and, thus, create a new protein signature.

Pages: 178 to 183

Copyright: Copyright (c) IARIA, 2014

Publication date: May 25, 2014

Published in: conference

ISSN: 2308-4197

ISBN: 978-1-61208-340-7

Location: Venice, Italy

Dates: from May 25, 2014 to May 29, 2014