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A deep learning approach for transgender and gender diverse patient identification in electronic health records.
Hua, Yining; Wang, Liqin; Nguyen, Vi; Rieu-Werden, Meghan; McDowell, Alex; Bates, David W; Foer, Dinah; Zhou, Li.
Afiliação
  • Hua Y; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Epidemiology, Harvard T.H Chan School of Public Health, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical Schoo
  • Wang L; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: lwang@bwh.harvard.edu.
  • Nguyen V; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: vnguyen31@bwh.harvard.edu.
  • Rieu-Werden M; Division of General Medicine, Massachusetts General Hospital, Boston, MA, USA. Electronic address: mrieuwerden@mgh.harvard.edu.
  • McDowell A; Health Policy Research Institute, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA; Department of Health Care Policy, Harvard Medical School, Boston, MA, USA. Electronic address: amcdowell4@mgh.harvard.edu.
  • Bates DW; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: dbates@bwh.harvard.edu.
  • Foer D; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Division of Allergy and Clinical Immunology, Department of Medicine, Brigham and Women's Hospital, USA. Electronic address: dfoer@bwh.harvard.edu.
  • Zhou L; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: lzhou@bwh.harvard.edu.
J Biomed Inform ; 147: 104507, 2023 11.
Article em En | MEDLINE | ID: mdl-37778672
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pessoas Transgênero / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article
Texto completo
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XML
PubMed Links
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pessoas Transgênero / Aprendizado Profundo Tipo de estudo: Diagnostic_studies / Prognostic_studies Limite: Adult / Female / Humans / Male Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2023 Tipo de documento: Article