MKI67 and breast cancer: The model’s AUC reached 0.77, with an average AUC of 0.72 for cross-validation, suggesting that the machine learning model based on the features derived from the malignant subregion could accurately and reliably predict Ki-67 expression levels, offering significant diagnostic value for breast cancer.