Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement

Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement

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In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing datasets of CXRs from COVID-19+ patients are relatively small, and r...

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Bibliographic Details
Main Authors: Anusua Trivedi, Caleb Robinson, Marian Blazes, Anthony Ortiz, Jocelyn Desbiens, Sunil Gupta, Rahul Dodhia, Pavan K. Bhatraju, W. Conrad Liles, Jayashree Kalpathy-Cramer, Aaron Y. Lee, Juan M. Lavista Ferres
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2022-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536609/?tool=EBI

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9536609/?tool=EBI

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