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. 2021 Mar 16;11:6006. doi: 10.1038/s41598-021-85570-2

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© The Author(s) 2021

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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DeepWrist pipeline. From left to right: a wrist radiograph is passed to ROI (region of interest) localization block, which predicts three landmark points (P1, P2 and P3). Subsequently, these landmarks are used to crop an ROI image from the original radiograph. Finally, we utilize a fracture detection block which predicts whether the radiograph is normal or has a fracture. In addition to the prediction, we generate an explanation of the decision using a GradCAM technique.