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. 2025 Jul 1;15:22394. doi: 10.1038/s41598-025-05527-7

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© The Author(s) 2025

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.

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Fig. 4 — Successful connection of the real-time microscopic field, smartphone and AI algorithm. The Betrue Real-time Microscopic Field Sharing System (RealVision System, Guangzhou Betrue Technology) was installed on a microscope, the microscopic field was connected with smartphone via WiFi, and then the smartphone was connected directly to AI algorithm (the Faster-RCNN network with a ResNet-50 backbone) on the server through 5G networks. Eventually, the AI results are sent back to the smartphone for confirmation by the pathologists.