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. 2019 Apr 12;9:5982. doi: 10.1038/s41598-019-42326-3

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© The Author(s) 2019

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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Comparison of the predictive value (c-index) and number of variables for the models developed in this paper versus representative models from the literature. Previous approaches are shown in yellow, with different symbols corresponding to different studies. ML methods described in this paper are shown in red and linear models in blue. Results are given for the best models in each reference and for the validation groups when available.