This paper is in the following e-collection/theme issue:

Machine Learning (1434) Decision Support for Health Professionals (1163) Imaging Informatics (190)

Published on in Vol 8, No 8 (2020): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/18089, first published .
Assessment of the Robustness of Convolutional Neural Networks in Labeling Noise by Using Chest X-Ray Images From Multiple Centers

Assessment of the Robustness of Convolutional Neural Networks in Labeling Noise by Using Chest X-Ray Images From Multiple Centers

Assessment of the Robustness of Convolutional Neural Networks in Labeling Noise by Using Chest X-Ray Images From Multiple Centers

Authors of this article:

Ryoungwoo Jang1 Author Orcid Image ;   Namkug Kim2 Author Orcid Image ;   Miso Jang1 Author Orcid Image ;   Kyung Hwa Lee1 Author Orcid Image ;   Sang Min Lee3 Author Orcid Image ;   Kyung Hee Lee4 Author Orcid Image ;   Han Na Noh5 Author Orcid Image ;   Joon Beom Seo3 Author Orcid Image
Article Authors Cited by (10) Tweetations (2) Metrics

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  8. Kim J, Ryu W, Kim D, Kim E. Better performance of deep learning pulmonary nodule detection using chest radiography with pixel level labels in reference to computed tomography: data quality matters. Scientific Reports 2024;14(1) View
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