Detection of Breast Cancer using Artificial Neural Network - Singh, Saveri; MA, Ansari; Batra, Naresh; Urooj, Shabana (International Journal of Psychosocial Rehabilitation, 2020)
Breast cancer is one of leading reasons and the second common cause of death among women all over the world. The simplified diagnosis of breast cancer is one of the significant, real world problems that has been faced in the field of medical science. Machine learning is gaining importance in diagnosis of abnormalities as it is a quick simple way for detection of diseases. In this work, we seek to explore the artificial intelligence techniques and machine learning approach to detect breast cancer. The method is applied to the Wisconsin Breast Cancer Dataset collected form the open source. The dataset consists of nine attributes that are used to train the network. The network used in the work is back-propagation. The simulation is done in Matlab software. The network classifies the input data into the two classes of cancer (benign or malignant) as result. The machine learning algorithm of back propagation seems to be an efficient terminology for the diagnosis of breast cancer.