Transfer learning-trained convolutional neural networks identify novel MRI biomarkers of Alzheimer's disease progression.

Li, Yi; Haber, Annat; Preuss, Christoph; John, Cai; Uyar, Asli; Yang, Hongtian Stanley; Logsdon, Benjamin A; Philip, Vivek; Karuturi, R Krishna Murthy; Carter, Gregory W

Li, Yi; Haber, Annat; Preuss, Christoph; John, Cai; Uyar, Asli; Yang, Hongtian Stanley; Logsdon, Benjamin A; Philip, Vivek; Karuturi, R Krishna Murthy; Carter, Gregory W.

Afiliação

Li Y; The Jackson Laboratory Farmington Connecticut USA.
Haber A; The Jackson Laboratory Farmington Connecticut USA.
Preuss C; The Jackson Laboratory Bar Harbor Maine USA.
John C; The Jackson Laboratory Farmington Connecticut USA.
Uyar A; The Jackson Laboratory Farmington Connecticut USA.
Yang HS; The Jackson Laboratory Bar Harbor Maine USA.
Logsdon BA; Sage Bionetworks Seattle Washington USA.
Philip V; The Jackson Laboratory Bar Harbor Maine USA.
Karuturi RKM; The Jackson Laboratory Farmington Connecticut USA.
Carter GW; The Jackson Laboratory Farmington Connecticut USA.

Alzheimers Dement (Amst) ; 13(1): e12140, 2021.

Article em En | MEDLINE | ID: mdl-34027015

Palavras-chave

Alzheimer's disease; convolutional neural networks; deep learning; disease progression; imaging phenotypes; machine learning; magnetic resonance imaging; transfer learning

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Texto completo: 1 Bases de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Alzheimers Dement (Amst) Ano de publicação: 2021 Tipo de documento: Article

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