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Correction

Correction: Deep fusion of gray level co-occurrence matrices for lung nodule classification

  • The PLOS One Editors

The articles cited in [1] as References 13, 15, and 52 were retracted after [1] was published due to concerns about potential manipulation of the publication process.

In addition, the LIDC-IDRI dataset citation [2] is missing from the ‘Dataset’ section and References list, and the Data Availability statement is incomplete and includes a link that is not currently functional. The Data Availability statement is updated to:

This study uses data obtained from the LUNGx and LIDC-IDRI datasets. The LIDC-IDRI dataset is available at https://www.cancerimagingarchive.net/collection/lidc-idri/. The LUNGx dataset is freely available from the following website: https://wiki.cancerimagingarchive.net/display/Public/LUNGx+SPIE-AAPM-NCI+Lung+Nodule+Classification+Challenge.

References

  1. 1. Saihood A, Karshenas H, Nilchi ARN. Deep fusion of gray level co-occurrence matrices for lung nodule classification. PLoS One. 2022;17(9):e0274516. pmid:36174073
  2. 2. Armato SG III, McLennan G, Bidaut L, McNitt-Gray MF, Meyer CR, Reeves AP, et al. Data From LIDC-IDRI [Data set]. The Cancer Imaging Archive. 2015.

Citation: The PLOS One Editors (2025) Correction: Deep fusion of gray level co-occurrence matrices for lung nodule classification. PLoS One 20(5): e0324959. https://doi.org/10.1371/journal.pone.0324959

Published: May 20, 2025

Copyright: © 2025 The PLOS One Editors. 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.