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Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI.

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Published in American Journal of Neuroradiology. 2013, vol. 34, no. 2, p. 283-291
Abstract BACKGROUND AND PURPOSE:MCI was recently subdivided into sd-aMCI, sd-fMCI, and md-aMCI. The current investigation aimed to discriminate between MCI subtypes by using DTI.MATERIALS AND METHODS:Sixty-six prospective participants were included: 18 with sd-aMCI, 13 with sd-fMCI, and 35 with md-aMCI. Statistics included group comparisons using TBSS and individual classification using SVMs.RESULTS:The group-level analysis revealed a decrease in FA in md-aMCI versus sd-aMCI in an extensive bilateral, right-dominant network, and a more pronounced reduction of FA in md-aMCI compared with sd-fMCI in right inferior fronto-occipital fasciculus and inferior longitudinal fasciculus. The comparison between sd-fMCI and sd-aMCI, as well as the analysis of the other diffusion parameters, yielded no significant group differences. The individual-level SVM analysis provided discrimination between the MCI subtypes with accuracies around 97%. The major limitation is the relatively small number of cases of MCI.CONCLUSIONS:Our data show that, at the group level, the md-aMCI subgroup has the most pronounced damage in white matter integrity. Individually, SVM analysis of white matter FA provided highly accurate classification of MCI subtypes.
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PMID: 22976235
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Research groups Démence du sujet âgé, troubles cognitifs, la symptomatologie cognitive (577)
Ischémie cérébrale et connectivité (801)
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HALLER, Sven et al. Individual Classification of Mild Cognitive Impairment Subtypes by Support Vector Machine Analysis of White Matter DTI. In: American Journal of Neuroradiology, 2013, vol. 34, n° 2, p. 283-291. https://archive-ouverte.unige.ch/unige:26363

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Deposited on : 2013-02-12

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