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. 2021 Nov 22;11:22636. doi: 10.1038/s41598-021-02168-4

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© The Author(s) 2021

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

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Performance of our model for detecting EBV + MSI/dMMR. ROC curves and AUCs (95%CI) are shown for UTokyo test cases (a) and TCGA test cases (b). This shows the performance of the model trained with data augmentation and the addition of a part of TCGA cases as training data. AUC- Area under the curve, CI- confidence interval, EBV- Epstein-Barr virus, MSI- microsatellite instability, dMMR- mismatch repair deficiency, ROC-Receiver operating characteristic curve, TCGA- The cancer genome atlas, UTokyo- University of Tokyo.