Weighted Majority Voting for Alzheimer's Disease Classification without Anatomical Regions of Interest

Abstract

We propose a method for Alzheimer's Disease classification without anatomical regions of interest. We perform a majority voting weighted by a prior distribution that is constructed based on a Boosting algorithm. Through the experiments, we demonstrate the effectiveness of the proposed method using Alzheimer's Disease Neuroimaging Initiative dataset.