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A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease
Abhinit Kumar Ambastha, Tze-Yun Leong, The Alzheimer's Disease Neuroimaging Initiative
1249
10.3233/978-1-61499-830-3-1249
Studies in Health Technology and Informatics
Volume 245: MEDINFO 2017: Precision Healthcare through Informatics
Abstract

Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and deep neural networks to identify salient structural correlations among brain regions that degenerate together in AD; this provides an understanding of how AD progresses in the brain. The proposed technique has a classification accuracy of 81.79% for AD against healthy subjects using a single modality imaging dataset.

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