We found four breast cancer risk prediction models that had been tested enough times to evaluate in detail. These were the Gail, Tyrer-Cuzick, BOADICEA, and BRCAPRO models. The BOADICEA model was one ...

Despite major advances in genetic testing for breast cancer risk prediction, death rates remain disproportionately high among women of African ancestry. This is often due to a combination of factors, ...

Researchers from Trinity College Dublin, St James's Hospital, and collaborating institutions have carried out the most ...

For women with a family history of breast cancer, existing breast cancer risk prediction models show similar modest ...

An artificial intelligence (AI) system that combines breast cancer tissue images with molecular marker data achieves high ...

Breast cancer is one of the most common malignancies worldwide, and mutations in the PI3K/AKT/mTOR (PAM) signaling pathway are prevalent in its development. Among these, PIK3CA mutations play a ...

Prognostic Significance of Isolated Tumor Cells and the Role of Immunohistochemistry in Nodal Evaluation in Breast Cancer: A SEER-Based Analysis and Reappraisal We used Monte Carlo simulation methods ...

Accurate detection of PIK3CA mutations is essential for personalizing breast cancer treatment, particularly with PI3K-targeted therapies. However, conventional molecular testing is not always ...

Federal density notification and state coverage expansions rely on BI-RADS density that labels 40–50% of women, limiting precision as a trigger for supplemental screening. Mirai derived 5-year ...

When 68-year-old retiree Ellen Costello received an email asking if she wanted to participate in a medical study about artificial intelligence and breast cancer, she hesitated at first. Did she really ...