Background Previous studies have explored the potential on radiomics features of primary
breast cancer tumor to identify axillary lymph node (ALN) metastasis. However, the value of …

The objective of this study is to develop a radiomic signature constructed from deep learning
features and a nomogram for prediction of axillary lymph node metastasis (ALNM) in breast …

Objective To investigate the value of predicting axillary lymph node (ALN) metastasis based
on intratumoral and peritumoral dynamic contrast-enhanced MRI (DCE-MRI) radiomics and …

Objective The aim of this study was to perform a meta‐analysis to evaluate the diagnostic
performance of machine learning (ML)-based radiomics of dynamic contrast-enhanced …

Rationale and Objectives Accurate identification of axillary lymph node (ALN) status in
breast cancer patients is important for determining treatment options and avoiding axillary …

Background Accurate diagnosis of breast lesions and discrimination of axillary lymph node
(ALN) metastases largely depend on radiologist experience. Purpose To develop a deep …

In breast cancer, undetected lymph node metastases can spread to distal parts of the body
for which the 5-year survival rate is only 27%, making accurate nodal metastases diagnosis …

Simple Summary Breast cancer represents the most frequent cancer in women in the world.
The state of the axillary lymph node is considered an independent prognostic factor and is …

Background Accurate evaluation of the axillary lymph node (ALN) status is needed for
determining the treatment protocol for breast cancer (BC). The value of magnetic resonance …

Background Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer
patients is essential for prognosis and treatment planning. Current radiological staging of …