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A machine learning approach for MRI-based classification of individuals with mild cognitive impairment
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Description: Diagnosis criteria for Mild Cognitive Impairment (MCI) rely on cognitive symptoms and do not require specific biomarker evidence of pathology. Nevertheless, patients may still have subtle brain changes that are identifiable with neuroimaging. To classify MCI patients vs. healthy age-matched controls, two algorithms—Multilayer Perceptron (MLP) and Support Vector Machine (SVM)—were applied to structural MRI data from the OASIS-1 cohort (https://www.oasis-brains.org/). Despite their comparable performance in some measures, the MLP algorithm was preferable due to superior recall of MCI cases.
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