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. 2020 Feb 26;3:23. doi: 10.1038/s41746-020-0232-8

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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. 3 — After reviewing the H&E whole-slide image (a), the pathologist extracts a tumor patch at ×10 objective magnification (b) and uploads it to the cloud-based model, which outputs predicted probabilities for cholangiocarcinoma (CC) and hepatocellular carcinoma (HCC) into the user interface (c), as well as corresponding class activation maps (not shown). These outputs are integrated with the pathologist’s diagnostic impression, to result in a final assisted diagnosis.