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...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Radiol Artif Intell
Hauptverfasser: 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.
Format: Artigo
Sprache:Inglês
Veröffentlicht: Radiological Society of North America 2020
Schlagworte:
Original Research
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7754832/
https://ncbi.nlm.nih.gov/pubmed/33928257
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1148/ryai.2020200098
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge