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Application of artificial intelligence in predicting lymph node metastasis in breast cancer
Breast cancer is a leading cause of death for women globally. A characteristic of breast cancer includes its ability to metastasize to distant regions of the body, and the disease achieves this through first spreading to the axillary lymph nodes. Traditional diagnosis of axillary lymph node metastas...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10364981/ https://www.ncbi.nlm.nih.gov/pubmed/37492388 http://dx.doi.org/10.3389/fradi.2023.928639 |
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author | Windsor, Gabrielle O. Bai, Harrison Lourenco, Ana P. Jiao, Zhicheng |
author_facet | Windsor, Gabrielle O. Bai, Harrison Lourenco, Ana P. Jiao, Zhicheng |
author_sort | Windsor, Gabrielle O. |
collection | PubMed |
description | Breast cancer is a leading cause of death for women globally. A characteristic of breast cancer includes its ability to metastasize to distant regions of the body, and the disease achieves this through first spreading to the axillary lymph nodes. Traditional diagnosis of axillary lymph node metastasis includes an invasive technique that leads to potential clinical complications for breast cancer patients. The rise of artificial intelligence in the medical imaging field has led to the creation of innovative deep learning models that can predict the metastatic status of axillary lymph nodes noninvasively, which would result in no unnecessary biopsies and dissections for patients. In this review, we discuss the success of various deep learning artificial intelligence models across multiple imaging modalities in their performance of predicting axillary lymph node metastasis. |
format | Online Article Text |
id | pubmed-10364981 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-103649812023-07-25 Application of artificial intelligence in predicting lymph node metastasis in breast cancer Windsor, Gabrielle O. Bai, Harrison Lourenco, Ana P. Jiao, Zhicheng Front Radiol Radiology Breast cancer is a leading cause of death for women globally. A characteristic of breast cancer includes its ability to metastasize to distant regions of the body, and the disease achieves this through first spreading to the axillary lymph nodes. Traditional diagnosis of axillary lymph node metastasis includes an invasive technique that leads to potential clinical complications for breast cancer patients. The rise of artificial intelligence in the medical imaging field has led to the creation of innovative deep learning models that can predict the metastatic status of axillary lymph nodes noninvasively, which would result in no unnecessary biopsies and dissections for patients. In this review, we discuss the success of various deep learning artificial intelligence models across multiple imaging modalities in their performance of predicting axillary lymph node metastasis. Frontiers Media S.A. 2023-02-20 /pmc/articles/PMC10364981/ /pubmed/37492388 http://dx.doi.org/10.3389/fradi.2023.928639 Text en © 2023 Windsor, Bai, Lourenco and Jiao. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Radiology Windsor, Gabrielle O. Bai, Harrison Lourenco, Ana P. Jiao, Zhicheng Application of artificial intelligence in predicting lymph node metastasis in breast cancer |
title | Application of artificial intelligence in predicting lymph node metastasis in breast cancer |
title_full | Application of artificial intelligence in predicting lymph node metastasis in breast cancer |
title_fullStr | Application of artificial intelligence in predicting lymph node metastasis in breast cancer |
title_full_unstemmed | Application of artificial intelligence in predicting lymph node metastasis in breast cancer |
title_short | Application of artificial intelligence in predicting lymph node metastasis in breast cancer |
title_sort | application of artificial intelligence in predicting lymph node metastasis in breast cancer |
topic | Radiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10364981/ https://www.ncbi.nlm.nih.gov/pubmed/37492388 http://dx.doi.org/10.3389/fradi.2023.928639 |
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