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. 2020 Nov 26;10:20630. doi: 10.1038/s41598-020-77296-4

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© The Author(s) 2020

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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Evaluation of the importance of features for conversion to MCI classification using the filter method SelectKBest. The 12 features most informative for MCI conversion are displayed in order of importance (increasing importance from bottom to top or from left to right). The target feature, conversion to MCI, is displayed in the last row/column. Pearson’s correlation among all pairs of features, including the output target (conversion to MCI), are shown when $r > 0.1$ . Only APOE and SCD correlate above this threshold.