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Comparison of four computer-aided diagnosis schemes for automated discrimination of myocardial heart disease

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1 Author(s)
Du-Yih Tsai ; Dept. of Radiol. Technol., Niigata Univ., Japan

The aim of this paper is to compare the performance of four different methods, i.e., neural network (NN) with backpropagation learning, NN with genetic-algorithm-based (GA-based) learning, fuzzy reasoning, and the GA-based fuzzy logic approach, for automated discrimination of myocardial heart disease. In our experiments, a total of 90 samples of echocardiographic images from 45 subjects were used. Our results showed that the GA-based fuzzy logic approach is superior to the other three methods. This method enables the classification to achieve a 95.9% of accuracy

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Signal Processing Proceedings, 2000. WCCC-ICSP 2000. 5th International Conference on  (Volume:3 )

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