Citation: Xiangtao Chen, Yuting Bai, Peng Wang, Jiawei Luo. Correction to 'Data augmentation based semi-supervised method to improve COVID-19 CT classification' [Mathematical Biosciences and Engineering 20(4) (2023) 6838–6852][J]. Mathematical Biosciences and Engineering, 2024, 21(12): 7854-7855. doi: 10.3934/mbe.2024345
| [1] | Xiangtao Chen, Yuting Bai, Peng Wang, Jiawei Luo . Data augmentation based semi-supervised method to improve COVID-19 CT classification. Mathematical Biosciences and Engineering, 2023, 20(4): 6838-6852. doi: 10.3934/mbe.2023294 |
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"Data augmentation based semi-supervised method to improve COVID-19 CT classification" [Mathematical Biosciences and Engineering 20(4) (2023) 6838–6852]
By Xiangtao Chen, Yuting Bai, Peng Wang and Jiawei Luo
DOI: 10.3934/mbe.2023294
Following publication, the authors have identified inappropriate references (References [3–5, 7, 10, 17]) included in the article [1]. To ensure the accuracy of our published work, we have decided to remove these references from the manuscript. The changes have no material impact on the conclusions of the article.
This correction has been approved by the Editor-in-Chief. We appreciate the support of the editorial office in ensuring the integrity of the published work.
We apologize for any inconvenience caused.
| [1] |
X. Chen, Y. Bai, P. Wang, J. Luo, Data augmentation based semi-supervised method to improve COVID-19 CT classification, Math. Biosci. Eng., 20 (2023), 6838–6852. https://doi.org/10.3934/mbe.2023294 doi: 10.3934/mbe.2023294
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Xiangtao Chen, Yuting Bai, Peng Wang, Jiawei Luo. Correction to "Data augmentation based semi-supervised method to improve COVID-19 CT classification" [Mathematical Biosciences and Engineering 20(4) (2023) 6838–6852][J]. Mathematical Biosciences and Engineering, 2024, 21(12): 7854-7855. doi: 10.3934/mbe.2024345
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