Cancer Management and Research (Mar 2020)

Prediction and Monitoring Method for Breast Cancer: A Case Study for Data from the University Hospital Centre of Coimbra

  • Yue J,
  • Zhao N,
  • Liu L

Journal volume & issue
Vol. Volume 12
pp. 1887 – 1893

Abstract

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Jin Yue, 1, 2,* Na Zhao, 3,* Liu Liu 1 1School of Mathematics and VC & VR Key Laboratory of Sichuan Province, Sichuan Normal University, Chengdu, People’s Republic of China; 2School of Mathematics, Sichuan University of Arts and Science, Dazhou, People’s Republic of China; 3Department of Clinical Laboratory and Guangdong Provincial Key Laboratory of Occupational Disease Prevention and Treatment, Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Liu Liu Email [email protected]: 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.Keywords: nonparametric, EWMA, rank-based method, breast cancer

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