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. 2019 Jul 31;9:11132. doi: 10.1038/s41598-019-47565-y

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© The Author(s) 2019

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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Feature importance. The panels display for all three types of testing the permutation accuracy as measure of feature importance (percentage increase in mean squared error [% Inc MSE]). Hereby, the outer nuclear layer (ONL) thickness was the most predictive feature for all three types of testing. Generally, thickness measurements exhibited higher feature importance as compare to the layer intensities. Abbreviations: infrared reflection (IR); retinal-pigment-epithelium-drusen-complex (RPEDC); photoreceptor outer segments (OS); inner segments (IS); inner retina (IRET); full retina (FRET); fundus-autofluorescence (FAF). The color indicates the putative structural correlates of the imaging features (red: inner retina; green: photoreceptors; blue: RPEDC; purple – summation images). Notably, information from all layers contributed towards the predictions.