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. 2020 Feb 27;10:3625. doi: 10.1038/s41598-020-60202-3

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© The Author(s) 2020

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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Top 16 semantic features based on the importance scores of features, measured via XGBoost, for predicting the EGFR mutation status. Were represented the features that have an average importance score greater than a 0.02. For each of the N = 100 runs, the importance score is determined and the average and standard deviation is displayed in the bar graph.