Predictive Detection of Breast Cancer with Artificial Neural Network and Support Vector Machine

The early detection of breast cancer is critical as it is the major cause of cancer in women. With an increase in population, the risk of death from breast cancer is also increasing, so, there is a need for a system that can automatically detect disease and aids medical health workers. The chapter contrasts the use of Machine Learning (ML) algorithms with two benchmark datasets, Wisconsin and the Coimbra datasets used to test the algorithms. The algorithm’s output is evaluated in terms of accuracy, precision, and recall. These techniques also provide the ROC and Area Under the Curve (AUC). According to the results, ANN beats SVM for both datasets giving an accuracy of 97.37% and 75% respectively.