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. 2018 Sep 5;8:13236. doi: 10.1038/s41598-018-31653-6

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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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Prediction of future development of AD. Five different classification machines were applied to predict future development of AD from MCI patients who have been followed for >3 years. In the ADNI cohort, consistent group classification performance was achieved across 5 different approaches (left). When the perfusion SPECT data was used, GLM, SSM/PCA1 and SSM/PCA2 classified both prodromal AD and stable MCI patients as AD. Desirable performance (sensitivity × specificity > 0.5) was achieved in both SVM methods (right). It should be noted that the AD diagnosis was based on clinical examination, thus misdiagnosis cannot be ruled out, and may have contributed to the low sensitivity. It should be also noted that the limited follow-up period may have hindered the specificity of the method, i.e., if a longer follow-up was available, some of the stable MCI patients who have been classified as AD may have actually developed AD.