Breast Cancer Classification and Recurrence Prediction Using Artificial Neural Networks and Machine Learning Techniques

Recent surveys indicate that breast cancer is an important factor in the mortality rate of women. During the recent years, the number of breast cancer patients in India has been increased by 30% and is expected to continue to rise. The early detection, classification, and prediction of cancer recurrence can save the lives of cancer patients. Breast cancer is caused when a collection of quickly dividing cells develop into a lump or excess mass in the breast tissue and eventually into a tumour. There are two types of tumours: benign (not cancerous) and malignant (cancerous). Patients with breast cancer who undergo treatment (recovery period) often experience recurrence after treatment. The study of the timing and contributing variables of cancer recurrence can lead to successful treatment intervention. This can be achieved using machine Learning models and ANNs for diagnosis and prediction. Screening and classification methods enable health care professionals to provide personalised treatments that improve outcomes and survival rates. As a result, it is aimed at classifying features into different categories with a higher degree of accuracy, precision, sensitivity, and specificity.