Background: It is important to be able to predict, for each individual patient, the likelihood of
later metastatic occurrence, because the prediction can guide treatment plans tailored to a …

Simple Summary It is important to be able to effectively predict the likelihood of breast
cancer metastasis to potentially help make treatment plans for a patient. We developed a …

Abstract Background Approximately 10%–15% of patients with breast cancer die of cancer
metastasis or recurrence, and early diagnosis of it can improve prognosis. Breast cancer …

Several prognosis prediction models have been developed for breast cancer (BC) patients
with curative surgery, but there is still an unmet need to precisely determine BC prognosis …

Distant recurrence of breast cancer results in high lifetime risks and low 5-year survival
rates. Early prediction of distant recurrent breast cancer could facilitate intervention and …

Background Breast cancer brain metastases (BCBM) are the most fatal, with limited survival
in all breast cancer distant metastases. These patients are deemed to be incurable. Thus …

Background Bone is the most common metastatic site of patients with advanced breast
cancer and the survival time is their primary concern; however, we lack accurate predictive …

Breast cancer (BC) was the most common malignant tumor in women, and breast infiltrating
ductal carcinoma (IDC) accounted for about 80% of all BC cases. BC patients who had bone …

Aim: Method: This research presents a model combining machine learning (ML) techniques
and eXplainable artificial intelligence (XAI) to predict breast cancer (BC) metastasis and …

PURPOSE Selection of appropriate adjuvant therapy to ultimately reduce the risk of breast
cancer (BC) recurrence is a challenge for medical oncologists. Several automated risk …