Cargando…
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...
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: | |
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 |
Ejemplares similares
-
Multi-Radiologist User Study for Artificial Intelligence-Guided Grading of COVID-19 Lung Disease Severity on Chest Radiographs
por: Li, Matthew D., et al.
Publicado: (2021) -
A Case Tracking System with Electronic Medical Record Integration to Automate Outcome Tracking for Radiologists
por: Alkasab, Tarik K., et al.
Publicado: (2009) -
Automated Assessment and Tracking of COVID-19 Pulmonary Disease Severity on Chest Radiographs using Convolutional Siamese Neural Networks
por: Li, Matthew D., et al.
Publicado: (2020) -
Assessing the Relationship Between Race, Language, and Surgical Admissions in the Emergency Department
por: Rigney, Grant H., et al.
Publicado: (2023) -
MRI Simulation Study Investigating Effects of Vessel Topology, Diffusion, and Susceptibility on Transverse Relaxation Rates Using a Cylinder Fork Model
por: Shazeeb, Mohammed Salman, et al.
Publicado: (2017)