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...

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Detalles Bibliográficos
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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Radiological Society of North America 2020
Materias:
Original Research
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

Internet

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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