文章基本信息

标题：Support Vector Machine-Based Classification of AD on Bootstrap Method
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作者：R. Viswanathan ; Dr. K. Perumal
期刊名称：International Journal of Innovative Research in Science, Engineering and Technology
印刷版ISSN：2347-6710
电子版ISSN：2319-8753
出版年度：2016
卷号：5
期号：12
页码：21313
DOI：10.15680/IJIRSET.2016.0512085
出版社：S&S Publications
摘要：To present and evaluate a new automated method based on support vector machine (SVM) classificationof whole-brain anatomical magnetic resonance imaging to discriminate between patients with Alzheimer’s disease(AD) and elderly control subjects. Here the main approach is based on the use of structural images of magneticimaging, mild cognitive impairments and AD patients to distinguish the normal controls between their phase images.Independent Component Analysis technique is used for extracting the features from the inputs of support vectormachine. Based upon the characteristics of gray matter extracted from each ROI, we used an SVM algorithm to classifythe accuracy, effectiveness, subjects and statistical procedures based on bootstrap resampling to ensure the robustnessof the results.
关键词：Alzheimer’s disease Diagnosis; ICA techniques; Support vector machine; Sensitivity;Specificity.