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Neuro-Imaging Machine Learning Techniques for Alzheimer's Disease Diagnosis
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Author(s): Gehad Ismail Sayed (Cairo University, Egypt & Scientific Research Group in Egypt (SRGE), Egypt)and Aboul Ella Hassanien (Cairo University, Egypt & Scientific Research Group in Egypt (SRGE), Egypt)
Copyright: 2017
Pages: 19
Source title:
Handbook of Research on Machine Learning Innovations and Trends
Source Author(s)/Editor(s): Aboul Ella Hassanien (Cairo University, Egypt)and Tarek Gaber (Suez Canal University, Egypt)
DOI: 10.4018/978-1-5225-2229-4.ch022
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Abstract
Alzheimer's disease (AD) is considered one of the most common dementia's forms affecting senior's age staring from 65 and over. The standard method for identifying AD are usually based on behavioral, neuropsychological and cognitive tests and sometimes followed by a brain scan. Advanced medical imagining modalities such as MRI and pattern recognition techniques are became good tools for predicting AD. In this chapter, an automatic AD diagnosis system from MRI images based on using machine learning tools is proposed. A bench mark dataset is used to evaluate the performance of the proposed system. The adopted dataset consists of 20 patients for each diagnosis case including cognitive impairment, Alzheimer's disease and normal. Several evaluation measurements are used to evaluate the robustness of the proposed diagnosis system. The experimental results reveal the good performance of the proposed system.
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