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. 2021 Jun 11;11:12353. doi: 10.1038/s41598-021-91614-4

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© The Author(s) 2021

Open AccessThis 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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The Receiver Operating Characteristic (ROC) curves for the 100 LSTM networks. The grey curves show the results for each of the 100 networks and the blue curve shows the median. The ensemble median Area Under the Curve (AUC) is 0.971 (the 25% and the 75% percentile are 0.963 and 0.975, respectively). A classifier with no better accuracy than chance would be expected to have an AUC of 0.5, while an AUC of 1 corresponds to a classifier with perfect accuracy. A value of $> 0.96$ indicates a classifier with excellent discriminatory ability⁷⁸. (Plotted with Matplotlib v3.2.1⁷⁵).