Predicting MCI Status From Multimodal Language Data Using Cascaded Classifiers.

Fraser, Kathleen C; Lundholm Fors, Kristina; Eckerström, Marie; Öhman, Fredrik; Kokkinakis, Dimitrios

Fraser, Kathleen C; Lundholm Fors, Kristina; Eckerström, Marie; Öhman, Fredrik; Kokkinakis, Dimitrios.

Afiliação

Fraser KC; Digital Technologies Research Centre, National Research Council Canada, Ottawa, ON, Canada.
Lundholm Fors K; Department of Swedish, University of Gothenburg, Gothenburg, Sweden.
Eckerström M; Department of Swedish, University of Gothenburg, Gothenburg, Sweden.
Öhman F; Institute of Neuroscience and Physiology, Sahlgrenska Academy, Gothenburg, Sweden.
Kokkinakis D; Institute of Neuroscience and Physiology, Sahlgrenska Academy, Gothenburg, Sweden.

Front Aging Neurosci ; 11: 205, 2019.

Article em En | MEDLINE | ID: mdl-31427959

Palavras-chave

early detection; eye-tracking; language; machine learning; mild cognitive impairment; multimodal; speech

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies / Screening_studies Idioma: En Revista: Front Aging Neurosci Ano de publicação: 2019 Tipo de documento: Article País de afiliação: Canadá

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