INTRODUCTION
breast cancer, cancer, Breast cancer, deaths, Machine learning
CANCER, BREAST CANCER, BREAST CANCER
Breast cancer is the most common type of cancer in women globally and the leading cause of cancer‐related deaths in women.Many different factors contribute to breast cancer, including lifestyle risk factors and genetic factors.Machine learning techniques have been extensively employed to create risk assessment models in order to obtain more efficient and accurate decision‐making for the identification of breast cancer, including least absolute shrinkage and selection operator (LASSO), support vector machines (SVMs), artificial neural networks (ANNs), and Bayesian networks (BNs).In order to provide a reference for risk assessment, we evaluated breast cancer risk using several statistical models. In addition, the discriminatory performances of the models established in this study were compared with the scores calculated from CKB model, Gail model and Tyrer–Cuzick models.