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Using computable knowledge mined from the literature to elucidate confounders for EHR-based pharmacovigilance.
Malec, Scott A; Wei, Peng; Bernstam, Elmer V; Boyce, Richard D; Cohen, Trevor.
Afiliação
  • Malec SA; University of Pittsburgh School of Medicine, Department of Biomedical Informatics, Pittsburgh, PA, United States. Electronic address: sam413@pitt.edu.
  • Wei P; The University of Texas MD Anderson Cancer Center, Department of Biostatistics, Houston, TX, United States.
  • Bernstam EV; University of Texas Health Science Center at Houston, School of Biomedical Informatics, Houston, TX, United States.
  • Boyce RD; University of Pittsburgh School of Medicine, Department of Biomedical Informatics, Pittsburgh, PA, United States.
  • Cohen T; University of Washington, Department of Biomedical Informatics and Medical Education, Seattle, WA, United States.
J Biomed Inform ; 117: 103719, 2021 05.
Article em En | MEDLINE | ID: mdl-33716168
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Farmacovigilância / Modelos Teóricos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Farmacovigilância / Modelos Teóricos Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article