Automated tracking of emergency department abdominal CT findings during the COVID-19 pandemic using natural language processing

PURPOSE: During the COVID-19 pandemic, emergency department (ED) volumes have fluctuated. We hypothesized that natural language processing (NLP) models could quantify changes in detection of acute abdominal pathology (acute appendicitis (AA), acute diverticulitis (AD), or bowel obstruction (BO)) on...

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Detalles Bibliográficos
Autores principales: Li, Matthew D., Wood, Peter A., Alkasab, Tarik K., Lev, Michael H., Kalpathy-Cramer, Jayashree, Succi, Marc D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Inc. 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8154187/
https://www.ncbi.nlm.nih.gov/pubmed/34062318
http://dx.doi.org/10.1016/j.ajem.2021.05.057

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8154187/
https://www.ncbi.nlm.nih.gov/pubmed/34062318
http://dx.doi.org/10.1016/j.ajem.2021.05.057

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