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In this paper, a hybrid approach was proposed which classified the test data with high accuracy and speed. At first, the data points were mapped to a range of 0 to 0.5 and, depending on the type of issue, they were divided to n regions. The accurate but slow algorithm was allocated to the regions close to (f(.)=0) decision function. For those regions which were far from decision function, a faster...
We introduce a novel approach for the automatic classification of FDG-PET scans of subjects with Alzheimers disease (AD) and Frontotemporal dementia (FTD). Unlike previous work in the literature which focuses on principal component analysis and predefined regions of interest, we propose the combined use of information gain and spatial proximity to group cortical pixels into empirically determined...
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