A Novel and Robust Breast Cancer classification based on Histopathological Images using Naive Bayes Classifier

Abstract

One of the most significant problems facing public health today, breast cancer is regarded as the primary reason for cancer-related mortality among females all over the world. Early detection of this condition can significantly help in boosting the likelihood of the patient surviving the illness. In this regard, the gold standard diagnostic procedure is the biopsy, which entails the collection of tissue samples for subsequent examination under the microscope. However, the histological examination of breast cancer is not a simple process, requires a significant amount of effort, and can result in a significant amount of disagreement among pathologists. Pathologists may therefore benefit from the assistance that an automatic diagnostic system can provide in terms of improving the efficiency of diagnostic procedures. In this study, we identified cases of breast cancer by employing the Naive Bayes (NB) method. The implementations of this machine learning method could most certainly help with breast cancer control efforts for identifying, predicting, and preventing the disease, as well as planning for health care.