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Data-driven classification of patients with primary progressive aphasia.
Nestor, Peter J; Sajjadi, Seyed Ahmad; Patterson, Karalyn. - : eScholarship, University of California, 2017
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Data-driven classification of patients with primary progressive aphasia
Abstract: Current diagnostic criteria classify primary progressive aphasia into three variants–semantic (sv), nonfluent (nfv) and logopenic (lv) PPA–though the adequacy of this scheme is debated. This study took a data-driven approach, applying k-means clustering to data from 43 PPA patients. The algorithm grouped patients based on similarities in language, semantic and non-linguistic cognitive scores. The optimum solution consisted of three groups. One group, almost exclusively those diagnosed as svPPA, displayed a selective semantic impairment. A second cluster, with impairments to speech production, repetition and syntactic processing, contained a majority of patients with nfvPPA but also some lvPPA patients. The final group exhibited more severe deficits to speech, repetition and syntax as well as semantic and other cognitive deficits. These results suggest that, amongst cases of non-semantic PPA, differentiation mainly reflects overall degree of language/cognitive impairment. The observed patterns were scarcely affected by inclusion/exclusion of non-linguistic cognitive scores.
Keyword: 1203 Language and Linguistics; 2805 Cognitive Neuroscience; 3205 Experimental and Cognitive Psychology; 3310 Linguistics and Language; 3616 Speech and Hearing; Alzheimer's disease; Frontotemporal dementia; Logopenic aphasia; Non-fluent aphasia; Primary progressive aphasia; Semantic dementia
URL: https://espace.library.uq.edu.au/view/UQ:657338e
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