Computer-aided diagnosis of gastric carcinoma based on probability neural network and feature selection
Ju Liu · Automation and Instrumentation · 2009
Based on signal to noise ratio and probabilistic neural network method and associated with experimental data,an analysis model in gastric carcinoma is presented.According to the available information,the samples of gastric carcinoma can be tested and analyzed.The signal to noise ratio is first calculated and ranked from big to small.Secondly,records in the database are chosen as a training set to build a probabilistic neural network model and the feature subset is selected according to accuracy.Finally,test set is to tes taccuracy of model.The model is implemented using MATLAB,and it can be generalized and applied to similar disease auxiliary diagnosis region.