Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department-Reference-Cited by-同舟云学术

Combining Initial Radiographs and Clinical Variables Improves Deep Learning Prognostication in Patients with COVID-19 from the Emergency Department

Published:2021-03-01 Issue:2 Volume:3 Page:e200098
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Kwon Young Joon (Fred)^ORCID,Toussie Danielle^ORCID,Finkelstein Mark^ORCID,Cedillo Mario A.^ORCID,Maron Samuel Z.^ORCID,Manna Sayan^ORCID,Voutsinas Nicholas^ORCID,Eber Corey^ORCID,Jacobi Adam^ORCID,Bernheim Adam,Gupta Yogesh Sean,Chung Michael S.^ORCID,Fayad Zahi A.^ORCID,Glicksberg Benjamin S.^ORCID,Oermann Eric K.^ORCID,Costa Anthony B.^ORCID

Funder

Radiological Society of North America

Medical Student Research grant and the National Institutes of Health

Publisher

Radiological Society of North America (RSNA)

Subject

General Medicine

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.2020200098

Reference36 articles.

1. Automated Triaging of Adult Chest Radiographs with Deep Artificial Neural Networks

2. Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy