Ultrasound imaging is a commonly used modality for breast cancer detection and diagnosis.
In this review, we summarize ultrasound imaging technologies and their clinical applications …

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 To develop a radiomic nomogram for preoperative prediction of axillary lymph
node (LN) metastasis in breast cancer patients. Methods Preoperative magnetic resonance …

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 …

Objectives To assess whether MRI can exclude axillary lymph node metastasis, potentially
replacing sentinel lymph node biopsy (SLNB), and consequently eliminating the risk of …

The aim of this study is to evaluate the role of convolutional neural network (CNN) in
predicting axillary lymph node metastasis, using a breast MRI dataset. An institutional review …

Background Despite that machine learning (ML)-based MRI has been evaluated for
diagnosis of axillary lymph node metastasis (ALNM) in breast cancer patients, diagnostic …

Objective: To establish a radiomics nomogram by integrating clinical risk factors and
radiomics features extracted from digital mammography (MG) images for pre-operative …

Background Axillary lymph node metastases (ALNM) is one of the most important prognostic
factors in breast cancer. Positron emission tomography/computed tomography (PET/CT) and …

OBJECTIVES: This study aims to develop and validate a radiomics nomogram based on
dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to noninvasively …