Open AccessRadiologist-supervised Transfer Learning
Author(s) -
Brian Hurt,
Meagan Rubel,
Evan Masutani,
Kathleen Jacobs,
Lewis Hahn,
Michael Horowitz,
Seth Kligerman,
Albert Hsiao
Publication year - 2021
Publication title -
journal of thoracic imaging
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 0.836
H-Index - 57
eISSN - 1536-0237
pISSN - 0883-5993
DOI - 10.1097/rti.0000000000000618
Subject(s) - medicine , radiography , pneumonia , receiver operating characteristic , convolutional neural network , transfer of learning , intubation , radiology , chest radiograph , area under the curve , artificial intelligence , surgery , computer science
To assess the potential of a transfer learning strategy leveraging radiologist supervision to enhance convolutional neural network-based (CNN) localization of pneumonia on radiographs and to further assess the prognostic value of CNN severity quantification on patients evaluated for COVID-19 pneumonia, for whom severity on the presenting radiograph is a known predictor of mortality and intubation.