Sizing tumors with TNM classifications and rough sets method

In this paper, medical decision support systems for TNM (tumor characteristics, lymph node involvement, and distant metastatic lesions) classification aiming to divide cancer patients to low and high risk patients are presented. In addition, the system also explained the decision in the form of IF-THEN rules and in this manner performed data mining and new knowledge discovery. The case studies show that the system is robust and not dependent on the database size and the noise. The accuracy was almost 80% which is comparable with the accuracy of physicians and much better then obtained with more conventional discriminant analysis (62% and 67%).