Abstract
This paper presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of the Alzheimer type dementia. The proposed methodology is based on the combination of support vector machine learning with linear kernels and classification trees. The classification tree technique allows to choose wisely the most discriminant set of voxels in the images. Thus, the classification tree produces a considerably improvement upon considering the support vector machine classifier only.
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Salas-Gonzalez, D. et al. (2009). Computer Aided Diagnosis of Alzheimer Disease Using Support Vector Machines and Classification Trees. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03040-6_51
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DOI: https://doi.org/10.1007/978-3-642-03040-6_51
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-03039-0
Online ISBN: 978-3-642-03040-6
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