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Investigation of the Utility of Features in a Clinical De-identification Model: A Demonstration Using EHR Pathology Reports for Advanced NSCLC Patients.

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第一作者： Tanmoy,Paul

第一单位： Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States.;Center for Biomedical Informatics, University of Missouri, Columbia, MO, United States.

作者： Tanmoy,Paul ^[1] ; Md Kamruz Zaman,Rana ^[2] ; Preethi Aishwarya,Tautam ^[3] ; Teja Venkat Pavan,Kotapati ^[3] ; Yaswitha,Jampani ^[2] ; Nitesh,Singh ^[2] ; Humayera,Islam ^[4] ; Vasanthi,Mandhadi ^[1] ; Vishakha,Sharma ^[5] ; Michael,Barnes ^[5] ; Richard D,Hammer ^[6] ; Abu Saleh Mohammad,Mosa ^[7]

作者单位： Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States.;Center for Biomedical Informatics, University of Missouri, Columbia, MO, United States. ^[1] Center for Biomedical Informatics, University of Missouri, Columbia, MO, United States.;Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO, United States. ^[2] Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO, United States. ^[3] Center for Biomedical Informatics, University of Missouri, Columbia, MO, United States.;Institute for Data Science and Informatics, University of Missouri, Columbia, MO, United States. ^[4] Roche Diagnostics, F. Hoffmann-La Roche, Santa Clara, CA, United States. ^[5] Department of Pathology and Anatomical Sciences, University of Missouri, Columbia, MO, United States. ^[6] Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO, United States.;Center for Biomedical Informatics, University of Missouri, Columbia, MO, United States.;Department of Health Management and Informatics, School of Medicine, University of Missouri, Columbia, MO, United States.;Institute for Data Science and Informatics, University of Missouri, Columbia, MO, United States. ^[7]

关键词 NLP clinical text de-identification conditional random field data warehousing de-identification named entity recognition protected health information

DOI 10.3389/fdgth.2022.728922

PMID 35252956

发布时间 2022-05-02

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Investigation of the Utility of Features in a Clinical De-identification Model: A Demonstration Using EHR Pathology Reports for Advanced NSCLC Patients.

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Investigation of the Utility of Features in a Clinical De-identification Model: A Demonstration Using EHR Pathology Reports for Advanced NSCLC Patients.

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