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Machine Learning Approach Identified Multi-Platform Factors for Caries Prediction in Child-Mother Dyads.
Wu, Tong Tong; Xiao, Jin; Sohn, Michael B; Fiscella, Kevin A; Gilbert, Christie; Grier, Alex; Gill, Ann L; Gill, Steve R.
Afiliação
  • Wu TT; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, United States.
  • Xiao J; Eastman Institute for Oral Health, University of Rochester Medical Center, Rochester, NY, United States.
  • Sohn MB; Department of Biostatistics and Computational Biology, University of Rochester Medical Center, Rochester, NY, United States.
  • Fiscella KA; Department of Family Medicine, University of Rochester Medical Center, Rochester, NY, United States.
  • Gilbert C; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States.
  • Grier A; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States.
  • Gill AL; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States.
  • Gill SR; Microbiology and Immunology, University of Rochester Medical Center, Rochester, NY, United States.
Front Cell Infect Microbiol ; 11: 727630, 2021.
Article em En | MEDLINE | ID: mdl-34490147
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cárie Dentária / Mães Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans Idioma: En Revista: Front Cell Infect Microbiol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cárie Dentária / Mães Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Child / Female / Humans Idioma: En Revista: Front Cell Infect Microbiol Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos