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Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department
PURPOSE: To train a deep learning classification algorithm to predict chest radiograph severity scores and clinical outcomes in patients with coronavirus disease 2019 (COVID-19). MATERIALS AND METHODS: In this retrospective cohort study, patients aged 21–50 years who presented to the emergency depar...
Autores principales: | Kwon, Young Joon (Fred), Toussie, Danielle, Finkelstein, Mark, Cedillo, Mario A., Maron, Samuel Z., Manna, Sayan, Voutsinas, Nicholas, Eber, Corey, Jacobi, Adam, Bernheim, Adam, Gupta, Yogesh Sean, Chung, Michael S., Fayad, Zahi A., Glicksberg, Benjamin S., Oermann, Eric K., Costa, Anthony B. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Radiological Society of North America
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754832/ https://www.ncbi.nlm.nih.gov/pubmed/33928257 http://dx.doi.org/10.1148/ryai.2020200098 |
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