title: Automatic Prediction of Conversion from Mild Cognitive Impairment to Probable Alzheimer's Disease using Structural Magnetic Resonance Imaging.
abstract: Mild Cognitive Impairment (MCI) is thought to be a precursor to the development of early Alzheimer's disease (AD). For early diagnosis of AD, the development of a model that is able to predict the conversion of amnestic MCI to AD is challenging. Using automatic whole-brain MRI analysis techniques and pattern classification methods, we developed a model to differentiate AD from healthy controls (HC), and then applied it to the prediction of MCI conversion to AD. Classification was performed using support vector machines (SVMs) together with a SVM-based feature selection method, which selected a set of most discriminating predictors for optimizing prediction accuracy. We obtained 90.5% cross-validation accuracy for classifying AD and HC, and 72.3% accuracy for predicting MCI conversion to AD. These analyses suggest that a classifier trained to separate HC vs. AD has substantial potential for predicting MCI conversion to AD.
authors.affiliation: Regenstrief Institute and Indiana University School of Medicine (IUSM), Indianapolis, IN.
authors.forename: Kwangsik
authors.initials: K
authors.lastname: Nho
authors.forename: Li
authors.initials: L
authors.lastname: Shen
authors.forename: Sungeun
authors.initials: S
authors.lastname: Kim
authors.forename: Shannon L
authors.initials: SL
authors.lastname: Risacher
authors.forename: John D
authors.initials: JD
authors.lastname: West
authors.forename: Tatiana
authors.initials: T
authors.lastname: Foroud
authors.forename: Clifford R
authors.initials: CR
authors.lastname: Jack
authors.forename: Michael W
authors.initials: MW
authors.lastname: Weiner
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Saykin
mesh_terms: D000544:Alzheimer Disease / Q000175:diagnosis; D001921:Brain; D060825:Cognitive Dysfunction; D006801:Humans; D008279:Magnetic Resonance Imaging; D011336:Probability