BACKGROUND: There are documented differences in Breast cancer (BrCA) presentations and outcomes between Black and White patients. In addition to molecular factors, socioeconomic, racial, and clinical factors result in disparities in outcomes for wome...
PURPOSE: Mucinous breast carcinoma (MBC) tends to be misdiagnosed as fibroadenomas (FA) due to its benign imaging characteristics. We aimed to develop a deep learning (DL) model to differentiate MBC and FA based on ultrasound (US) images. The model c...
BACKGROUND: To explore whether the combination of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and nonmono-exponential (NME) model-based diffusion-weighted imaging (DWI) via deep neural network (DNN) can improve the prediction of ...
BACKGROUND: The incidence of breast cancer ranks highest among cancers and is exceedingly heterogeneous. Immunohistochemical staining is commonly used clinically to identify the molecular subtype for subsequent treatment and prognosis.
BACKGROUND: Breast cancer is a leading cause of cancer morbility and mortality in women. The possibility of overtreatment or inappropriate treatment exists, and methods for evaluating prognosis need to be improved.
OBJECTIVES: Ultrasound examination has inter-observer and intra-observer variability and a high false-positive rate. The aim of this study was to evaluate the value of the combined use of a deep learning-based computer-aided diagnosis (CAD) system an...
BACKGROUND: Accurate assessment of the axillary lymph nodes (aLNs) in breast cancer patients is essential for prognosis and treatment planning. Current radiological staging of nodal metastasis has poor accuracy. This study aimed to investigate the ma...
BACKGROUND: Incidental breast cancers can be detected on chest computed tomography (CT) scans. With the use of deep learning, the sensitivity of incidental breast cancer detection on chest CT would improve. This study aimed to evaluate the performanc...
BACKGROUND: The objective of this study was to investigate the relationship of aerobic fitness (AF) at diagnosis, before treatment and its relationship with body composition, physical function, lipidic profile, comorbidities, tumor characteristics, a...