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. 2024 Jul 19;8:151. doi: 10.1038/s41698-024-00652-4

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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. 8 — Heatmap analysis (a–c) of three samples from the Ovarian dataset correctly classified by both ADA and AIDA methods. The first column is the input slide incorporating the tumor annotation provided by the pathologist, and the second and third columns are the outputs of ADA and AIDA methods. The closer it is to red, the more likely it is to be classified as a ground truth label, while the closer it is to blue, the less likely it is.