Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Open Access

Correction

Correction: Prediction of the ectasia screening index from raw Casia2 volume data for keratoconus identification by using convolutional neural networks

  • Maziar Mirsalehi,
  • Benjamin Fassbind,
  • Andreas Streich,
  • Achim Langenbucher

In the Results subsection of the Abstract, there is an error in the last sentence of the paragraph. The correct sentence is: In the classification task, the three networks yielded an accuracy of 94.81%, 95.27% and 95.83%, respectively; a sensitivity of 92.08%, 94.64% and 94.17%, respectively; a specificity of 96.61%, 95.69% and 96.92%, respectively; a positive predictive value of 94.72%, 93.55% and 95.28%, respectively; and a F1 score of 93.38%, 94.09% and 94.73%, respectively.

In Table 4, the accuracy and sensitivity value for adapted ResNet 18, and F1 score value for adapted EfficientNetB0 are incorrect. Please see the correct Table 4 here.

thumbnail
Download:
Table 4. Evaluation metrics for CNN architectures. Abbreviations: CNN = Convolutional Neural Network, PPV = Positive Predictive Value.

https://doi.org/10.1371/journal.pone.0351460.t004

Reference

  1. 1. Mirsalehi M, Fassbind B, Streich A, Langenbucher A. Prediction of the ectasia screening index from raw Casia2 volume data for keratoconus identification by using convolutional neural networks. PLoS One. 2025;20(9):e0311036. pmid:40892937

Citation: Mirsalehi M, Fassbind B, Streich A, Langenbucher A (2026) Correction: Prediction of the ectasia screening index from raw Casia2 volume data for keratoconus identification by using convolutional neural networks. PLoS One 21(6): e0351460. https://doi.org/10.1371/journal.pone.0351460

Published: June 9, 2026

Copyright: © 2026 Mirsalehi 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.