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. 2019 Aug 29;9:12529. doi: 10.1038/s41598-019-48738-5

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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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Prediction of tumor growth curve. (a) Two-layer feedforward network with a sigmoid transfer function in the hidden layer and linear transfer function in the output layer. Tumor growth is different between the different tumor types. (b) Growth curve of the three different tumor type with the experimental data, the fitted exponential growth model and the predicted growth curve from the neural network. (c,d) Growth curve of each tumor type. Data is shown as mean ± standard deviation.