Prediction and monitoring method for breast cancer: A case study for data from the university hospital centre of coimbra

Abstract

Breast cancer is the second most common cancer in women after skin cancer. Breast cancer can occur in both men and women, but it is far more common in women. Real-time monitoring of breast cancer indicators is becoming increasingly important. It can help create advances in the diagnosis and treatment of breast cancer. In this paper, we provide a nonparametric statistical method to predict and detect breast cancer occur. The exponentially weighted moving average (EWMA) control scheme is based on rank methods so that it is completely nonparametric. It is efficient in detecting the shifts for multivariate processes. A real example data from the University Hospital Centre of Coimbra is given to illustrate this method.