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Optimizing research in symptomatic uterine fibroids with development of a computable phenotype for use with electronic health records.
Hoffman, Sarah R; Vines, Anissa I; Halladay, Jacqueline R; Pfaff, Emily; Schiff, Lauren; Westreich, Daniel; Sundaresan, Aditi; Johnson, La-Shell; Nicholson, Wanda K.
Afiliação
  • Hoffman SR; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC.
  • Vines AI; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC.
  • Halladay JR; Department of Family Medicine, University of North Carolina, Chapel Hill, NC.
  • Pfaff E; North Carolina Translational and Clinical Sciences Institute, University of North Carolina, Chapel Hill, NC.
  • Schiff L; Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, NC.
  • Westreich D; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC.
  • Sundaresan A; Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, NC; Center for Health Promotion and Disease Prevention, University of North Carolina, Chapel Hill, NC.
  • Johnson LS; Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, NC; Center for Health Promotion and Disease Prevention, University of North Carolina, Chapel Hill, NC.
  • Nicholson WK; Department of Obstetrics and Gynecology, University of North Carolina, Chapel Hill, NC; Center for Women's Health Research, University of North Carolina, Chapel Hill, NC; Program on Women's Endocrine and Reproductive Health, School of Medicine, University of North Carolina, Chapel Hill, NC; Center f
Am J Obstet Gynecol ; 218(6): 610.e1-610.e7, 2018 06.
Article em En | MEDLINE | ID: mdl-29432754
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Uterinas / Algoritmos / Registros Eletrônicos de Saúde / Leiomioma Idioma: En Ano de publicação: 2018 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias Uterinas / Algoritmos / Registros Eletrônicos de Saúde / Leiomioma Idioma: En Ano de publicação: 2018 Tipo de documento: Article