Early detection of disease has emerged as a critical issue in recent years due to the fast population increase seen in
medical research. The chance of dying from breast cancer increases dramatically as the world’s population continues to increase
at an alarming rate. Compared to other cancers discovered thus far, breast cancer is the second most severe. In addition to
assisting medical staff in disease diagnosis, an automated disease detection system also provides reliable, effective, and fast
intervention, which reduces the likelihood of mortality. In this research study, the Artificial Neural Network is employed for
breast cancer classification. The model is validated on well-known dataset comprised from UCI machine learning repository.
The results reveal that the ANNs obtained the highest accuracy i.e. 98.24%.
