Cargando…
Natural Language Processing and Machine Learning for Detection of Respiratory Illness by Chest CT Imaging and Tracking of COVID-19 Pandemic in the US
BACKGROUND: Coronavirus disease 2019 (COVID-19) has spread quickly throughout the United States (US) causing significant disruption in healthcare and society. Tools to identify hot spots are important for public health planning. The goal of our study was to determine if natural language processing (...
Autores principales: | Cury, Ricardo C., Megyeri, Istvan, Lindsey, Tony, Macedo, Robson, Batlle, Juan, Kim, Shwan, Baker, Brian, Harris, Robert, Clark, Reese H. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Radiological Society of North America
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7977750/ https://www.ncbi.nlm.nih.gov/pubmed/33778666 http://dx.doi.org/10.1148/ryct.2021200596 |
Ejemplares similares
-
When is the use of contrast media in chest CT indicated?
por: Hochhegger, Bruno, et al.
Publicado: (2017) -
Role of Chest CT in COVID-19
por: Malguria, Nagina, et al.
Publicado: (2021) -
Natural language processing to convert unstructured COVID-19 chest-CT reports into structured reports
por: Fanni, Salvatore Claudio, et al.
Publicado: (2023) -
Clinical characteristics and chest CT imaging features of critically ill COVID-19 patients
por: Zhang, Nan, et al.
Publicado: (2020) -
CT angiography of abdomen and pelvis in critically ill COVID-19 patients: imaging findings and correlation with the CT chest score
por: Vadvala, Harshna V., et al.
Publicado: (2021)