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. 2018 Feb 21;8:3395. doi: 10.1038/s41598-018-21758-3

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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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Kaplan-Meier survival curves based on different predictors for 420 colorectal cancer patients. We dichotomized patients into Low Risk group (blue curve) and High Risk group (Red curve) by median value of each predictor independently. The LSTM model predictor yields stronger stratification with a Hazard Ratio (HR) of 2.3 (log rank p-value < 0.0001) as compared to Visual Scoring on a tissue microarray (TMA) spot level (HR 1.67; log rank p-value = 0.00016) and histological grade on a whole-slide level (HR 1.65; log rank p-value = 0.00016). Dukes’ stage also stratifies the patients into groups with significantly different outcome (p-value < 0.0001). Dukes’ stage remains a stronger predictor of survival, but is not directly comparable to the tissue-based variables, since it includes extent of local invasion, number of lymph nodes affected and whether distant metastasis is observed.