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. 2018 Jul 6;8:10231. doi: 10.1038/s41598-018-28611-7

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© The Author(s) 2018

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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Variable importance in AI and CI prediction. Variable importance for AI (a) and CI (b). Based on Fig. 2 models for AI and CI prediction, the diagrams shows each variable’s influence on models. We used vector cosine similarity to evaluate SLEDAI’s relation with other variables in equations and it showed that SLEDAI is comparably an independent variable in AI and CI equations.