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. 2020 Feb 26;10:3485. doi: 10.1038/s41598-020-60595-1

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© The Author(s) 2020

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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External validation. (A) ADNI and ANM1 (B) ADNI and ANM2 (C) ANM1 and ADNI (D) ANM1 and ANM2 (E) ANM2 and ADNI (F) ANM2 and ANM1 are arranged as training and testing dataset, respectively. The y-axes in each graph show performance measured by AUC. One star denotes a model with the best performance among five classifiers, and two stars denote the best model among five classifiers and five feature selection methods. The number indicates the number of selected genes in each feature selection method. AUC, area under the curve; AD, Alzheimer’s disease; ADNI, Alzheimer’s Disease Neuroimaging Initiative; ANM, AddNeuroMed.