Predicting Working Memory in Healthy Older Adults Using Real-Life Language and Social Context Information: A Machine Learning Approach.

Ferrario, Andrea; Luo, Minxia; Polsinelli, Angelina J; Moseley, Suzanne A; Mehl, Matthias R; Yordanova, Kristina; Martin, Mike; Demiray, Burcu

Ferrario, Andrea; Luo, Minxia; Polsinelli, Angelina J; Moseley, Suzanne A; Mehl, Matthias R; Yordanova, Kristina; Martin, Mike; Demiray, Burcu.

Afiliação

Ferrario A; Chair of Technology Marketing, ETH Zurich, Zurich, Switzerland.
Luo M; Mobiliar Lab for Analytics, ETH Zurich, Zurich, Switzerland.
Polsinelli AJ; Department of Psychology, University of Zurich, Zurich, Switzerland.
Moseley SA; University Research Priority Program Dynamics of Healthy Aging, University of Zurich, Zurich, Switzerland.
Mehl MR; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, United States.
Yordanova K; Department of Psychology, Minnesota Epilepsy Group, St Paul, MN, United States.
Martin M; Department of Psychology, University of Arizona, Tucson, AZ, United States.
Demiray B; Institute of Computer Science, University of Rostock, Rostock, Germany.

JMIR Aging ; 5(1): e28333, 2022 Mar 08.

Article em En | MEDLINE | ID: mdl-35258457

Palavras-chave

Electronically Activated Recorder (EAR); behavioral indicators; cognitive aging; language complexity; machine learning; natural language processing; social context

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Idioma: En Revista: JMIR Aging Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Suíça País de publicação: Canadá

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