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

Machine Learning (1465) Decision Support for Health Professionals (1185) Imaging Informatics (193)

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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  3. Ursuleanu T, Luca A, Gheorghe L, Grigorovici R, Iancu S, Hlusneac M, Preda C, Grigorovici A. Deep Learning Application for Analyzing of Constituents and Their Correlations in the Interpretations of Medical Images. Diagnostics 2021;11(8):1373 View
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  5. Akhter Y, Singh R, Vatsa M. AI-based radiodiagnosis using chest X-rays: A review. Frontiers in Big Data 2023;6 View
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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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