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Artificial intelligence in breast imaging: Current situation and clinical challenges

Breast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer‐related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast c...

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Autores principales: You, Chao, Shen, Yiyuan, Sun, Shiyun, Zhou, Jiayin, Li, Jiawei, Su, Guanhua, Michalopoulou, Eleni, Peng, Weijun, Gu, Yajia, Guo, Weisheng, Cao, Heqi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582610/
https://www.ncbi.nlm.nih.gov/pubmed/37933287
http://dx.doi.org/10.1002/EXP.20230007
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author You, Chao
Shen, Yiyuan
Sun, Shiyun
Zhou, Jiayin
Li, Jiawei
Su, Guanhua
Michalopoulou, Eleni
Peng, Weijun
Gu, Yajia
Guo, Weisheng
Cao, Heqi
author_facet You, Chao
Shen, Yiyuan
Sun, Shiyun
Zhou, Jiayin
Li, Jiawei
Su, Guanhua
Michalopoulou, Eleni
Peng, Weijun
Gu, Yajia
Guo, Weisheng
Cao, Heqi
author_sort You, Chao
collection PubMed
description Breast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer‐related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast cancer makes it necessary to deeply mine and rationally utilize the tremendous amount of breast imaging information. With the rapid advancement of computer science, artificial intelligence (AI) has been noted to have great advantages in processing and mining of image information. Therefore, a growing number of scholars have started to focus on and research the utility of AI in breast imaging. Here, an overview of breast imaging databases and recent advances in AI research are provided, the challenges and problems in this field are discussed, and then constructive advice is further provided for ongoing scientific developments from the perspective of the National Natural Science Foundation of China.
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spelling pubmed-105826102023-11-05 Artificial intelligence in breast imaging: Current situation and clinical challenges You, Chao Shen, Yiyuan Sun, Shiyun Zhou, Jiayin Li, Jiawei Su, Guanhua Michalopoulou, Eleni Peng, Weijun Gu, Yajia Guo, Weisheng Cao, Heqi Exploration (Beijing) Reviews Breast cancer ranks among the most prevalent malignant tumours and is the primary contributor to cancer‐related deaths in women. Breast imaging is essential for screening, diagnosis, and therapeutic surveillance. With the increasing demand for precision medicine, the heterogeneous nature of breast cancer makes it necessary to deeply mine and rationally utilize the tremendous amount of breast imaging information. With the rapid advancement of computer science, artificial intelligence (AI) has been noted to have great advantages in processing and mining of image information. Therefore, a growing number of scholars have started to focus on and research the utility of AI in breast imaging. Here, an overview of breast imaging databases and recent advances in AI research are provided, the challenges and problems in this field are discussed, and then constructive advice is further provided for ongoing scientific developments from the perspective of the National Natural Science Foundation of China. John Wiley and Sons Inc. 2023-07-20 /pmc/articles/PMC10582610/ /pubmed/37933287 http://dx.doi.org/10.1002/EXP.20230007 Text en © 2023 The Authors. Exploration published by Henan University and John Wiley & Sons Australia, Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Reviews
You, Chao
Shen, Yiyuan
Sun, Shiyun
Zhou, Jiayin
Li, Jiawei
Su, Guanhua
Michalopoulou, Eleni
Peng, Weijun
Gu, Yajia
Guo, Weisheng
Cao, Heqi
Artificial intelligence in breast imaging: Current situation and clinical challenges
title Artificial intelligence in breast imaging: Current situation and clinical challenges
title_full Artificial intelligence in breast imaging: Current situation and clinical challenges
title_fullStr Artificial intelligence in breast imaging: Current situation and clinical challenges
title_full_unstemmed Artificial intelligence in breast imaging: Current situation and clinical challenges
title_short Artificial intelligence in breast imaging: Current situation and clinical challenges
title_sort artificial intelligence in breast imaging: current situation and clinical challenges
topic Reviews
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10582610/
https://www.ncbi.nlm.nih.gov/pubmed/37933287
http://dx.doi.org/10.1002/EXP.20230007
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