Predicting treatment-related cardiovascular risks in breast cancer patients: development and validation of an interpretable machine learning model
Development and validate an interpretable machine learning model to predict the 1- to 3-year risk of cardiovascular events in breast cancer patients by integrating baseline and treatment variables and identified endocrine therapy, anemia management therapy, and history of cerebrovascular disease as the top three predictors.