Application of artificial intelligence in predicting lymph node metastasis in breast cancer.

Gabrielle O Windsor, Harrison Bai, Ana P Lourenco, Zhicheng Jiao
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引用次数: 0

Abstract

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.

Abstract Image

人工智能在乳腺癌淋巴结转移预测中的应用。
乳腺癌是全球妇女死亡的主要原因。乳腺癌的一个特点是它有能力转移到身体的远处,而这种疾病是通过首先扩散到腋窝淋巴结来实现的。腋窝淋巴结转移的传统诊断包括一种侵入性技术,这可能导致乳腺癌患者的临床并发症。人工智能在医学成像领域的兴起导致了创新的深度学习模型的创建,这些模型可以无创地预测腋窝淋巴结的转移状态,这将导致患者无需进行不必要的活检和解剖。在这篇综述中,我们讨论了各种深度学习人工智能模型在多种成像模式下预测腋窝淋巴结转移的成功。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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