Prognosis System for Lung Cancer Based on Rough Set Theory

Currently, lung cancer, as a kind of malignant tumor, is the No. one killer of human health. The incidence and mortality of it have the fastest growth. Prognostic factors for lung cancer are very complicated, but most studies only report a few prognostic factors. In this paper, a prognostic system is constructed based on rough sets. It collects all possible factors, finds relevant prognostic factors under different conditions through the reduction algorithm and makes rules to guide clinic. The article gives the systematic processing procedure, main functions, core algorithms and some possible prognostic factors for lung cancer. Practice shows that applying this system to predicting the prognosis of lung cancer is a feasible approach.