Natural Language Processing for Information Extraction of Gastric Diseases and Its Application in Large-Scale Clinical Research

Background and Aims: The utility of clinical information from esophagogastroduodenoscopy (EGD) reports has been limited because of its unstructured narrative format. We developed a natural language processing (NLP) pipeline that automatically extracts information about gastric diseases from unstruct...

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Detalles Bibliográficos
Autores principales: Song, Gyuseon, Chung, Su Jin, Seo, Ji Yeon, Yang, Sun Young, Jin, Eun Hyo, Chung, Goh Eun, Shim, Sung Ryul, Sa, Soonok, Hong, Moongi Simon, Kim, Kang Hyun, Jang, Eunchan, Lee, Chae Won, Bae, Jung Ho, Han, Hyun Wook
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9181010/
https://www.ncbi.nlm.nih.gov/pubmed/35683353
http://dx.doi.org/10.3390/jcm11112967

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9181010/
https://www.ncbi.nlm.nih.gov/pubmed/35683353
http://dx.doi.org/10.3390/jcm11112967

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