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. 2021 Jul 7;11:14057. doi: 10.1038/s41598-021-92072-8

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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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Kaplan–Meier (KM) Curves for Overall Survival (OS). The figure shows the KM curves for OS outcome stratified by the cluster label over (a) training and (b) test data. For the training, the patients were grouped using Hierarchical Clustering over the co-occurrence matrix from the Random Survival Forest. For the testing, the patients were assigned to a cluster by applying the regression model trained for predicting the cluster labels using the top radiomic features identified by the random survival forest. For both training and testing, the KM curves are significantly different which indicates that the proposed clustering is effective in identifying a risk stratification and can be effectively used as a predictive covariate.