Machine learning based hierarchical classification of frontotemporal dementia and Alzheimer's disease
Abstract
In a clinical setting, an individual subject classification model rather than a group analysis would be more informative. Specifically, the subtlety of cortical atrophy in some frontotemporal dementia (FTD) patients and overlapping patterns of atrophy among three FTD clinical syndromes including behavioral variant FTD (bvFTD), non-fluent/agrammatic variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA) give rise to the...
Paper Details
Title
Machine learning based hierarchical classification of frontotemporal dementia and Alzheimer's disease
Published Date
Jan 1, 2019
Journal
Volume
23
Pages
101811 - 101811
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