Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6269617 | Journal of Neuroscience Methods | 2011 | 8 Pages |
Abstract
⺠A novel application of automatic classification methods from computer science to improve the accuracy of detecting Mild Cognitive Impairment during the Visual Paired Comparison task. ⺠An effective representation of eye movement characteristics such as fixations, saccades, and re-fixations as features for automatic classification algorithms. ⺠Our techniques allow to automatically distinguish age-matched normal control subjects from MCI subjects with 87% accuracy, 96% sensitivity and 77% specificity, compared to the best classification performance of 67% accuracy, 60% sensitivity, and 73% with previous techniques over VPC data.
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Authors
Dmitry Lagun, Cecelia Manzanares, Stuart M. Zola, Elizabeth A. Buffalo, Eugene Agichtein,