Purpose To develop a machine learning model that allows high-risk breast lesions (HRLs)
diagnosed with image-guided needle biopsy that require surgical excision to be …

Importance Following recent US Food and Drug Administration approval, adoption of whole
slide imaging in clinical settings may be imminent, and diagnostic accuracy, particularly …

Background Upgrade rates of high-risk breast lesions after screening mammography were
examined. Methods The Breast Cancer Surveillance Consortium registry was used to …

Motivation Identifying carcinoma subtype can help to select appropriate treatment options
and determining the subtype of benign lesions can be beneficial to estimate the patients' risk …

Background Recent mammography-based risk models can estimate short-term or long-term
breast cancer risk, but whether risk assessment may improve by combining these models …

Background As artificial intelligence methods for the diagnosis of disease advance, we
aimed to evaluate machine learning in the predictive task of distinguishing between …

The categorization of intraductal proliferative lesions of the breast based on routine light
microscopic examination of histopathologic sections is in many cases challenging, even for …

A major limitation of screening breast ultrasound (US) is a substantial number of false-
positive biopsy. This study aimed to develop a deep learning-based computer-aided …

Background For patients with early-stage breast cancers, neoadjuvant treatment is
recommended for non-luminal tumors instead of luminal tumors. Preoperative distinguish …

BACKGROUND: Discriminating malignant breast lesions from benign ones and accurately
predicting the risk of breast cancer for individual patients are crucial to successful clinical …