Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
558665 | Digital Signal Processing | 2007 | 8 Pages |
The use of machine learning tools in medical diagnosis is increasing gradually. This is mainly because the effectiveness of classification and recognition systems has improved in a great deal to help medical experts in diagnosing diseases. Such a disease is breast cancer, which is a very common type of cancer among woman. In this paper, breast cancer diagnosis was conducted using least square support vector machine (LS-SVM) classifier algorithm. The robustness of the LS-SVM is examined using classification accuracy, analysis of sensitivity and specificity, k-fold cross-validation method and confusion matrix. The obtained classification accuracy is 98.53% and it is very promising compared to the previously reported classification techniques. Consequently, by LS-SVM, the obtained results show that the used method can make an effective interpretation and point out the ability of design of a new intelligent assistance diagnosis system.