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Open Access

Correction

Correction: Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort

  • Eun Young Kim,
  • Young Jae Kim,
  • Won-Jun Choi,
  • Gi Pyo Lee,
  • Ye Ra Choi,
  • Kwang Nam Jin,
  • Young Jun Cho

There are errors in the Competing Interests statement. The correct Competing Interests statement is as follows: KNJ has received research grant funding from Lunit Inc. for activities not related to the present article. This does not alter our adherence to PLOS ONE policies on sharing data and materials. Other authors have no potential conflicts of interest to disclose.

Reference

  1. 1. Kim EY, Kim YJ, Choi W- J, Lee GP, Choi YR, Jin KN, et al. (2021) Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort. PLoS ONE 16(2): e0246472. https://doi.org/10.1371/journal.pone.0246472 pmid:33606779

Citation: Kim EY, Kim YJ, Choi W-J, Lee GP, Choi YR, Jin KN, et al. (2021) Correction: Performance of a deep-learning algorithm for referable thoracic abnormalities on chest radiographs: A multicenter study of a health screening cohort. PLoS ONE 16(4): e0251045. https://doi.org/10.1371/journal.pone.0251045

Published: April 28, 2021

Copyright: © 2021 Kim et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.