Machine learning-driven ultrasound radiomics for assessing axillary lymph node burden in breast cancer

Machine learning-driven ultrasound radiomics for assessing axillary lymph node burden in breast cancer

ObjectiveThis study explores the value of combining intratumoral and peritumoral radiomics features from ultrasound imaging with clinical characteristics to assess axillary lymph node burden in breast cancer patients.MethodsA total of 131 breast cancer patients with axillary lymph node metastasis (A...

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Bibliographic Details
Main Authors: Si-Rui Wang, Feng Tian, Tong Zhu, Chun-Li Cao, Jin-Li Wang, Wen-Xiao Li, Jun Li, Ji-Xue Hou
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Endocrinology
Subjects:
breast cancer
ultrasound
axillary lymph nodes burden
radiomics
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fendo.2025.1548888/full
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https://www.frontiersin.org/articles/10.3389/fendo.2025.1548888/full

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