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Identifying Information Gaps in Electronic Health Records by Using Natural Language Processing: Gynecologic Surgery History Identification.
Moon, Sungrim; Carlson, Luke A; Moser, Ethan D; Agnikula Kshatriya, Bhavani Singh; Smith, Carin Y; Rocca, Walter A; Gazzuola Rocca, Liliana; Bielinski, Suzette J; Liu, Hongfang; Larson, Nicholas B.
Afiliação
  • Moon S; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Carlson LA; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Moser ED; Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States.
  • Agnikula Kshatriya BS; Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, MN, United States.
  • Smith CY; Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States.
  • Rocca WA; Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States.
  • Gazzuola Rocca L; Department of Neurology, Mayo Clinic, Rochester, MN, United States.
  • Bielinski SJ; Women's Health Research Center, Mayo Clinic, Rochester, MN, United States.
  • Liu H; Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States.
  • Larson NB; Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, United States.
J Med Internet Res ; 24(1): e29015, 2022 01 28.
Article em En | MEDLINE | ID: mdl-35089141
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Processamento de Linguagem Natural / Registros Eletrônicos de Saúde Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 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: Processamento de Linguagem Natural / Registros Eletrônicos de Saúde Tipo de estudo: Diagnostic_studies / Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: J Med Internet Res Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos