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. 2023 May 22;13:8213. doi: 10.1038/s41598-023-34943-w

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© The Author(s) 2023

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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Summary of individual classifier performance on the Iba-1 microglia dataset during the validation stage. A chart of the most and least accurate three incrementally trained classifiers, ranked by F1 score of 25 trained classifiers (n = 10 images). Error bars represent standard error of the mean on calculated performance statistics from each image, where the statistic itself is calculated from total cells in the dataset. The parameters used in ACCT: 0.5 threshold, 50 minimum pixel size, and 1,000 maximum pixel size.