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Predicting rapid cognitive decline in Alzheimer's disease patients using quantitative EEG markers and

Carmina Reyes-Coronel, Markus Waser, Heinrich Garn

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |March 9, 2017
    PubMed

    Abstract:

    Alzheimer's Disease (AD) can take different courses: some patients remain relatively stable while others decline rapidly within a given period of time. Losing more than 3 Mini-Mental State Examination (MMSE) points in one year is classified as rapid cognitive decline (RCD). This study used neuropsychological test scores and quantitative EEG (QEEG) markers obtained at a baseline examination to identify if an AD patient will be suffering from RCD. Data from 68 AD patients of the multi-centric cohort study PRODEM-Austria were applied. 15 of the patients were classified into the RCD group. RCD versus non-RCD support vector machine (SVM) classifiers using QEEG markers as predictors obtained 72.1% and 77.9% accuracy ratings based on leave-one-out validation. Adding neuropsychological test scores of Boston Naming Test improved the classifier to 80.9% accuracy, 80% sensitivity, and 81.1% specificity. These results indicate that QEEG markers together with neuropsychological test scores can be used as RCD predictors.

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