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An automated algorithm using free-text clinical notes to improve identification of transgender people.

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第一作者： Fagen,Xie

第一单位： Department of Research and Evaluation, Kaiser Permanente Southern California Medical Group , Pasadena, California, USA.

作者： Fagen,Xie ^[1] ; Darios,Getahun ^[1] ; Virginia P,Quinn ^[1] ; Theresa M,Im ^[1] ; Richard,Contreras ^[1] ; Michael J,Silverberg ^[2] ; Tisha C,Baird ^[3] ; Rebecca,Nash ^[4] ; Lee,Cromwell ^[5] ; Douglas,Roblin ^[6] ; Trenton,Hoffman ^[4] ; Michael,Goodman ^[4]

作者单位： Department of Research and Evaluation, Kaiser Permanente Southern California Medical Group , Pasadena, California, USA. ^[1] Division of Research, Kaiser Permanente , Oakland, California, USA. ^[2] Department of Endocrinology, Kaiser Permanente Los Angeles Medical Center , Los Angeles, California, USA. ^[3] Department of Epidemiology, Emory University School of Public Health , Atlanta, Georgia, USA. ^[4] Center for Clinical and Outcomes Research, Kaiser Permanente Georgia , Atlanta, Georgia, USA. ^[5] School of Public Health, Georgia State University , Atlanta, Georgia, USA. ^[6]

关键词 Transgender computerized algorithm natural language processing rule-based

医学主题词算法(Algorithms);数据挖掘(Data Mining);电子健康病历(Electronic Health Records);人类(Humans);结果可重复性(Reproducibility of Results);男(雄)性(Male);女(雌)性(Female)

DOI 10.1080/17538157.2020.1828890

PMID 33203265

发布时间 2025-03-31

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