An application of Takagi-Sugeno fuzzy system to the classification of cancer patients based on elemental contents in serum samples
A Takagi-Sugeno fuzzy system was applied to the discriminations of lung cancer, liver cancer and stomach cancer patients from normal persons based on trace elemental contents in serum samples. Results showed that better classifications could be achieved using this method. Fuzzy logic is a generalization of classical logic, in which there is a smooth transition from true to false. Neural network (NN) learning technique can automate this process and substantially reduce the development time and cost while improving the performance. The combination of the fuzzy logic and NN yields a new fuzzy approach. Takagi-Sugeno fuzzy system combined neural networks with fuzzy logic. So its application range is greatly enlarged and the performance is also improved. (c) 2005 Elsevier B.V. All rights reserved.
takagi-sugeno fuzzy system cancer serum neural network