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. 2022 Jul 6;12:11440. doi: 10.1038/s41598-022-15634-4

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© The Author(s) 2022

Open AccessThis 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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GradCam analysis of kidney Cyst, Normal, Stone and Tumor class photos at the final convolution layer in the Inception v3, Vgg16, and Resnet models. First row: shows the Gradcam images from inception v3 model for different classes. Second row: shows the Gradcam images from Resnet50 model for different classes. Third row: shows the Gradcam images from Vgg16 model for different classes. The GradCam activation mapping for the xray image is shown in the second row. The first, second, third, and fourth columns are for kidney cysts, normal, stone, and tumor classes respectively.