Background: Breast cancer continues to be a significant global health issue, necessitating
advancements in prevention and early detection strategies. This review aims to assess and …

Background: Artificial intelligence (AI) algorithms can be applied in breast cancer risk
prediction and prevention by using patient history, scans, imaging information, and analysis …

Despite the deployment of specific breast cancer screening strategies, breast cancer
incidence rates have escalated significantly over recent decades. In a bid to reverse this …

Background Breast cancer is the leading cause of cancer-related fatalities among women
worldwide. Conventional screening and risk prediction models primarily rely on …

Introduction This large case-control study explored the application of machine learning
models to identify risk factors for primary invasive incident breast cancer (BC) in the Iranian …

Breast cancer has the highest incidence and second-highest mortality rate among all
cancers. The management of breast cancer is being revolutionized by artificial intelligence …

Breast cancer is a significant cause of cancer-related mortality in women worldwide. Early
and precise diagnosis is crucial, and clinical outcomes can be markedly enhanced. The rise …

Accurate and individualized breast cancer risk assessment can be used to guide
personalized screening and prevention recommendations. Existing risk prediction models …

Breast cancer (BC) is a major health concern worldwide. It is a complex and multifactorial
disease, and identifying its risk factors is crucial for early detection and effective treatment …

Background Artificial intelligence (AI) has the potential to personalize treatment strategies for
patients with cancer. However, current methodological weaknesses could limit clinical …