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. 2020 Dec 3;10:21149. doi: 10.1038/s41598-020-77875-5

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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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Comparisons of receiver operating characteristic curve analysis for distinguishing responders and non-responders between conventional PET/MRI parameters and convolutional neural network methods. SUV0 versus PET0 (a), SUV1 versus PET1 (b), ADC0 versus MRI0 (c), and ADC1 versus MRI1 (d). SUV standardized uptake value, PET positron emission tomography, ADC apparent diffusion coefficient, MRI magnetic resonance imaging.