A certified de-identification system for all clinical text documents for information extraction at scale.

Radhakrishnan, Lakshmi; Schenk, Gundolf; Muenzen, Kathleen; Oskotsky, Boris; Ashouri Choshali, Habibeh; Plunkett, Thomas; Israni, Sharat; Butte, Atul J

Radhakrishnan, Lakshmi; Schenk, Gundolf; Muenzen, Kathleen; Oskotsky, Boris; Ashouri Choshali, Habibeh; Plunkett, Thomas; Israni, Sharat; Butte, Atul J.

Afiliação

Radhakrishnan L; Academic Research Services, Information Technology, University of California, San Francisco, San Francisco, California, USA.
Schenk G; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
Muenzen K; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
Oskotsky B; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
Ashouri Choshali H; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
Plunkett T; ArcherHall LLC, Sacramento, California, USA.
Israni S; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.
Butte AJ; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California, USA.

JAMIA Open ; 6(3): ooad045, 2023 Oct.

Article em En | MEDLINE | ID: mdl-37416449

Palavras-chave

Philter; clinical note text; de-identification; unstructured data

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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Guideline / Prognostic_studies Idioma: En Revista: JAMIA Open Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

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