Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers

Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers

Recent work has indicated the potential utility of automated language analysis for the detection of mild cognitive impairment (MCI). Most studies combining language processing and machine learning for the prediction of MCI focus on a single language task; here, we consider a cascaded approach to com...

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Bibliographic Details
Main Authors: Kathleen C. Fraser, Kristina Lundholm Fors, Marie Eckerström, Fredrik Öhman, Dimitrios Kokkinakis
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-08-01
Series:Frontiers in Aging Neuroscience
Subjects:
mild cognitive impairment
language
speech
eye-tracking
machine learning
multimodal
Online Access:https://www.frontiersin.org/article/10.3389/fnagi.2019.00205/full

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https://www.frontiersin.org/article/10.3389/fnagi.2019.00205/full

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