Deep learning (DL) is one of the most powerful data-driven machine-learning techniques in
artificial intelligence (AI). It can automatically learn from raw data without manual feature …

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 …

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 …

Background Multiparametric magnetic resonance imaging (MRI) is widely used in breast
cancer screening. Accurate prediction of the axillary lymph nodes metastasis (ALNM) is …

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

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 …

Newly diagnosed breast cancer (BC) patients with clinical T1–T2 N0 disease undergo
sentinel-lymph-node (SLN) biopsy, although most of them have a benign SLN. The pilot …

Objectives Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2+ breast
cancer. New measures are needed for a precise risk stratification to guide (de-) escalation of …

Purpose To develop a custom deep convolutional neural network (CNN) for noninvasive
prediction of breast cancer nodal metastasis. Materials and Methods This retrospective study …