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Accurate Identification of Colonoscopy Quality and Polyp Findings Using Natural Language Processing

OBJECTIVES: The aim of this study was to test the ability of a commercially-available NLP tool to accurately extract exam quality-related and large polyp information from colonoscopy reports with varying report formats. BACKGROUND: Colonoscopy quality reporting often requires manual data abstraction...

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Detalhes bibliográficos
Publicado no:J Clin Gastroenterol
Main Authors: Lee, Jeffrey K., Jensen, Christopher D., Levin, Theodore R., Zauber, Ann G., Doubeni, Chyke A., Zhao, Wei K., Corley, Douglas A.
Formato: Artigo
Idioma:Inglês
Publicado em: 2019
Assuntos:
Acesso em linha:https://ncbi.nlm.nih.gov/pmc/articles/PMC5847417/
https://ncbi.nlm.nih.gov/pubmed/28906424
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1097/MCG.0000000000000929
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