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Are we there yet? A machine learning architecture to predict organotropic metastases.
Skaro, Michael; Hill, Marcus; Zhou, Yi; Quinn, Shannon; Davis, Melissa B; Sboner, Andrea; Murph, Mandi; Arnold, Jonathan.
Afiliação
  • Skaro M; Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA. Michael.Skaro@uga.edu.
  • Hill M; Department of Computer Science, University of Georgia, Athens, GA, 30602, USA.
  • Zhou Y; Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA.
  • Quinn S; Institute of Bioinformatics, University of Georgia, Athens, GA, 30602, USA.
  • Davis MB; Department of Computer Science, University of Georgia, Athens, GA, 30602, USA.
  • Sboner A; Department of Cellular Biology, University of Georgia, Athens, GA, 30602, USA.
  • Murph M; Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, NY, 10065, USA.
  • Arnold J; Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital-Weill Cornell Medicine, New York, NY, 10065, USA.
BMC Med Genomics ; 14(1): 281, 2021 11 24.
Article em En | MEDLINE | ID: mdl-34819069
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Aprendizado de Máquina / Neoplasias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2021 Tipo de documento: Article