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. 2021 Sep 15;4:137. doi: 10.1038/s41746-021-00503-7

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© The Author(s) 2021

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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Fig. 4 — Receiver operator characteristics for the correct compression classification per ultrasound sequence/anatomical landmark on EVS1 (a). Confusion matrices (b) at optimal thresholds (* in (a)) per fold. Frame colours correspond to ROC fold colours in (a). Vessel status is extracted automatically through the ML models from the 121 available anatomical landmark sequences in EVS1.