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. 2018 Sep 4;4:32. doi: 10.1038/s41523-018-0084-4

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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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Fig. 2 — Digital stain for regions predicted to be ER-negative. Pixels are shaded red in regions predicted to be ER-negative with probability greater than 50%. Enlarged regions of ER-negative tissue (left) reveal that the network classifies sub-regions of epithelial tissue as ER-negative. For comparison, ER-positive tissue is shown (right)