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. 2023 Jan 10;13:485. doi: 10.1038/s41598-023-27548-w

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© The Author(s) 2023

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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Text analytics based on clinical notes of breast cancer patients (a) A text mining framework for detecting cancer using blood profile data. (b) A pie chart depicting the proportion of patients who have metastasis and lymph node involvement. (c) A pie chart depicting the percentage of disseminated cancer cells in the liver, bone, and brain of patients with metastatic breast cancer. (d) Venn diagram representing the number of medical records intersecting between "metas" and bone, brain, and liver.