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editorial

. 2024 Dec 20;18:37. doi: 10.1186/s13037-024-00422-y

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© The Author(s) 2024

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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Fig. 5 — Deep learning-based artificial intelligence computer vision model for automated detection of surgical tools and instruments for improved post-surgery count accuracy and prevention of unintentionally retained foreign bodies. © Deol ES, et al., 2024. Reproduced with permission by the Creative Commons Attribution 4.0 International License, from: Deol ES, et al., Artificial intelligence model for automated surgical instrument detection and counting: an experimental proof-of-concept study. Patient Saf. Surg. 2024, 18:24