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. 2020 May 24;10:162. doi: 10.1038/s41398-020-0836-4

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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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Fig. 1 — a Receiver operating characteristics (ROC) plot derived from the linear discriminate analysis (LDA) using blood-based markers based on the top finding from PLS approach. ROC plot of sensitivity (true positive rate) vs. 1-specificity (false positive rate) based on a LDA build upon the six markers with the highest contribution as determined by the PLS discriminant analysis. b ROC plot derived from the LDA using cognitive markers based on the top finding from PLS approach. ROC plot of sensitivity (true positive rate) versus 1-specificity (false positive rate) based on a LDA build upon the six markers with the highest contribution as determined by the PLS discriminant analysis. c ROC plot derived from the LDA using blood-based markers and cognitive markers based on the top finding from PLS approach. ROC plot of sensitivity (true positive rate) vs. 1-specificity (false positive rate) based on a LDA build upon the six markers with the highest contribution as determined by the PLS discriminant analysis.