Utilizing longitudinal microbiome taxonomic profiles to predict food allergy via Long Short-Term Memory networks.

Metwally, Ahmed A; Yu, Philip S; Reiman, Derek; Dai, Yang; Finn, Patricia W; Perkins, David L

Metwally, Ahmed A; Yu, Philip S; Reiman, Derek; Dai, Yang; Finn, Patricia W; Perkins, David L.

Afiliação

Metwally AA; Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Yu PS; Department of Computer Science, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Reiman D; Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Dai Y; Department of Computer Science, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Finn PW; Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Perkins DL; Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, United States of America.

PLoS Comput Biol ; 15(2): e1006693, 2019 02.

Article em En | MEDLINE | ID: mdl-30716085

Assuntos

Classificação/métodos; Previsões/métodos; Hipersensibilidade Alimentar/genética; Humanos; Estudos Longitudinais; Aprendizado de Máquina; Memória de Longo Prazo/fisiologia; Memória de Curto Prazo/fisiologia; Microbiota; Redes Neurais de Computação; Máquina de Vetores de Suporte

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2019 Tipo de documento: Article

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