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Machine Learning Approaches to Retrieve High-Quality, Clinically Relevant Evidence From the Biomedical Literature: Systematic Review.
Abdelkader, Wael; Navarro, Tamara; Parrish, Rick; Cotoi, Chris; Germini, Federico; Iorio, Alfonso; Haynes, R Brian; Lokker, Cynthia.
Afiliação
  • Abdelkader W; Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
  • Navarro T; Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
  • Parrish R; Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
  • Cotoi C; Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
  • Germini F; Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
  • Iorio A; Department of Medicine, McMaster University, Hamilton, ON, Canada.
  • Haynes RB; Health Information Research Unit, Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada.
  • Lokker C; Department of Medicine, McMaster University, Hamilton, ON, Canada.
JMIR Med Inform ; 9(9): e30401, 2021 Sep 09.
Article em En | MEDLINE | ID: mdl-34499041
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Systematic_reviews 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 Tipo de estudo: Prognostic_studies / Systematic_reviews Idioma: En Ano de publicação: 2021 Tipo de documento: Article