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Current Alzheimer Research

Editor-in-Chief

ISSN (Print): 1567-2050
ISSN (Online): 1875-5828

Computer based Classification of MR Scans in First Time Applicant Alzheimer Patients

Author(s): Fatma Polat, Selcuk Orhan Demirel, Omer Kitis, Fatma Simsek, Damla Isman Haznedaroglu, Kerry Coburn, Emre Kumral and Ali Saffet Gonul

Volume 9, Issue 7, 2012

Page: [789 - 794] Pages: 6

DOI: 10.2174/156720512802455359

Price: $65

Abstract

In this study, we aimed to classify MR images for recognizing Alzheimer Disease (AD) in a group of patients who were recently diagnosed by clinical history and neuropsychiatric exams by using non-biased machine-learning techniques. T1 weighted MRI scans of 31 patients with probable AD and 31 age- and gender-matched cognitively normal elderly were analyzed with voxel-based morphometry and classified by support vector machine (SVM), a machine learning technique. SVM could differentiate patients from controls with accuracy of 74 % (sensitivity: 70 % and specificity: 77 %) when the whole brain was included the analyses. The classification accuracy was increased to 79 % (sensitivity: 65 % and specificity: 93 %) when the analyses restricted to hippocampus. Our results showed that SVM is a promising tool for diagnosis of AD, but needed to be improved.

Keywords: Alzheimer’s disease, classification, diagnoses, support vector machines, hippocampus, magnetic resonance imaging, hippocampus, cardiovascular disease.


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