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人工智能在乳腺癌中的应用及未来展望。

Artificial intelligence in breast cancer: application and future perspectives.

机构信息

The Affiliated Lihuili Hospital of Ningbo University, Ningbo, 315000, Zhejiang, China.

出版信息

J Cancer Res Clin Oncol. 2023 Nov;149(17):16179-16190. doi: 10.1007/s00432-023-05337-2. Epub 2023 Sep 1.

DOI:10.1007/s00432-023-05337-2
PMID:37656245
Abstract

Breast cancer is one of the most common cancers and is one of the leading causes of cancer-related deaths in women worldwide. Early diagnosis and treatment are the key for a favorable prognosis. The application of artificial intelligence technology in the medical field is increasingly extensive, including image analysis, automated diagnosis, intelligent pharmaceutical system, personalized treatment and so on. AI-based breast cancer imaging, pathology and adjuvant therapy technology cannot only reduce the workload of clinicians, but also continuously improve the accuracy and sensitivity of breast cancer diagnosis and treatment. This paper reviews the application of AI in breast cancer, as well as looks ahead and poses challenges to the future development of AI for breast cancer detection and therapeutic, so as to provide ideas for future research.

摘要

乳腺癌是最常见的癌症之一,也是全球女性癌症相关死亡的主要原因之一。早期诊断和治疗是获得良好预后的关键。人工智能技术在医学领域的应用越来越广泛,包括图像分析、自动诊断、智能制药系统、个性化治疗等。基于人工智能的乳腺癌成像、病理学和辅助治疗技术不仅可以减轻临床医生的工作量,还可以不断提高乳腺癌诊断和治疗的准确性和敏感性。本文综述了人工智能在乳腺癌中的应用,并对人工智能在乳腺癌检测和治疗中的未来发展进行了展望和挑战,为未来的研究提供了思路。

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本文引用的文献

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The utilization of artificial intelligence applications to improve breast cancer detection and prognosis.利用人工智能应用提高乳腺癌的检测和预后。
Saudi Med J. 2023 Feb;44(2):119-127. doi: 10.15537/smj.2023.44.2.20220611.
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Artificial intelligence scale-invariant feature transform algorithm-based system to improve the calculation accuracy of Ki-67 index in invasive breast cancer: a multicenter retrospective study.基于人工智能尺度不变特征变换算法的系统提高浸润性乳腺癌中Ki-67指数的计算准确性:一项多中心回顾性研究
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Improving breast cancer diagnostics with deep learning for MRI.
Diagnosis of clear cell renal cell carcinoma via a deep learning model with whole-slide images.
通过基于全切片图像的深度学习模型诊断透明细胞肾细胞癌。
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Weight-adjusted-waist index: an innovative indicator of breast cancer hazard.体重调整腰围指数:乳腺癌风险的创新指标。
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Innovations in Artificial Intelligence-Driven Breast Cancer Survival Prediction: A Narrative Review.人工智能驱动的乳腺癌生存预测创新:一项叙述性综述。
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Advancements in triple-negative breast cancer sub-typing, diagnosis and treatment with assistance of artificial intelligence : a focused review.人工智能辅助三阴性乳腺癌亚分型、诊断和治疗的进展:重点综述。
J Cancer Res Clin Oncol. 2024 Aug 6;150(8):383. doi: 10.1007/s00432-024-05903-2.
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Awareness and intention-to-use of digital health applications, artificial intelligence and blockchain technology in breast cancer care.乳腺癌护理中数字健康应用程序、人工智能和区块链技术的认知度及使用意愿。
Front Med (Lausanne). 2024 May 2;11:1380940. doi: 10.3389/fmed.2024.1380940. eCollection 2024.
深度学习在 MRI 乳腺癌诊断中的应用。
Sci Transl Med. 2022 Sep 28;14(664):eabo4802. doi: 10.1126/scitranslmed.abo4802.
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A narrative review on current imaging applications of artificial intelligence and radiomics in oncology: focus on the three most common cancers.一篇关于人工智能和放射组学在肿瘤学中当前成像应用的叙述性综述:重点关注三种最常见的癌症。
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Stand-Alone Use of Artificial Intelligence for Digital Mammography and Digital Breast Tomosynthesis Screening: A Retrospective Evaluation.人工智能在数字乳腺 X 线摄影和数字乳腺断层合成筛查中的独立应用:一项回顾性评估。
Radiology. 2022 Mar;302(3):535-542. doi: 10.1148/radiol.211590. Epub 2021 Dec 14.