z-logo
open-access-imgOpen Access
An interpretable multi-task system for clinically applicable COVID-19 diagnosis using CXR
Author(s) -
Yan Zhuang,
Md Fashiar Rahman,
Yuxin Wen,
Michael Pokojovy,
Peter Mccaffrey,
Alexander H. Vo,
Eric Walser,
Scott T. Moen,
Honglun Xu,
Tzu-Liang Tseng
Publication year - 2022
Publication title -
journal of x-ray science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.357
H-Index - 32
eISSN - 1095-9114
pISSN - 0895-3996
DOI - 10.3233/xst-221151
Subject(s) - artificial intelligence , preprocessor , covid-19 , computer science , task (project management) , transfer of learning , pneumonia , pattern recognition (psychology) , sensitivity (control systems) , deep learning , machine learning , medicine , pathology , disease , management , electronic engineering , infectious disease (medical specialty) , engineering , economics

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here