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. 2019 Jun 21;2:56. doi: 10.1038/s41746-019-0131-z

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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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Fig. 3 — SMILY search accuracy from large-scale quantitative evaluation using pathologist-provided annotations. a Results for histologic feature match in prostate specimens, in comparison with a traditional image feature extractor (scale-invariant feature transform, SIFT) and random search. b Results for prostate cancer Gleason grade and histologic feature match, in comparison with the same baselines. Error bars indicate 95% confidence intervals (Methods)