GenNet framework: interpretable deep learning for predicting phenotypes from genetic data.

van Hilten, Arno; Kushner, Steven A; Kayser, Manfred; Ikram, M Arfan; Adams, Hieab H H; Klaver, Caroline C W; Niessen, Wiro J; Roshchupkin, Gennady V

van Hilten, Arno; Kushner, Steven A; Kayser, Manfred; Ikram, M Arfan; Adams, Hieab H H; Klaver, Caroline C W; Niessen, Wiro J; Roshchupkin, Gennady V.

Afiliação

van Hilten A; Department of Radiology and Nuclear Medicine, Erasmus MC, Medical Center, Rotterdam, the Netherlands. a.vanhilten@erasmusmc.nl.
Kushner SA; Department of Psychiatry, Erasmus MC, Medical Center, Rotterdam, the Netherlands.
Kayser M; Department of Genetic Identification, Erasmus MC, Medical Center, Rotterdam, the Netherlands.
Ikram MA; Department of Epidemiology, Erasmus MC, Medical Center, Rotterdam, the Netherlands.
Adams HHH; Department of Radiology and Nuclear Medicine, Erasmus MC, Medical Center, Rotterdam, the Netherlands.
Klaver CCW; Department of Clinical Genetics, Erasmus MC, Medical Center, Rotterdam, the Netherlands.
Niessen WJ; Department of Epidemiology, Erasmus MC, Medical Center, Rotterdam, the Netherlands.
Roshchupkin GV; Department of Ophthalmology, Erasmus MC, Medical Center, Rotterdam, the Netherlands.

Commun Biol ; 4(1): 1094, 2021 09 17.

Article em En | MEDLINE | ID: mdl-34535759

Assuntos

Aprendizado Profundo; Redes Neurais de Computação; Fenótipo; Humanos

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fenótipo / Redes Neurais de Computação / Aprendizado Profundo Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Commun Biol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Holanda

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