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- W2392279436 abstract "It is very important to make early diagnosis with breast tissue disease.The method based on Electrical Impedance Spectroscopy is effective for the clinical diagnosis.Advantages of the method include low-cost and non-damage.In this paper,we focused on the early automatic diagnosis of breast tissue disease based on two intelligent classifiers;BP network and support vector machine(SVM).The data of Electrical Impedance Spectroscopy come from 64 subjects,including 106 breast tissue samples.Focus on the uncertain property of selecting characters of the classifiers,parameter optimization and selecting were conducted based on the Genetic Algorithm.Based on principle of the overall optimization and the survival of the fittest,selection-crossover-mutation was done to pursue the optical parameters.After the process,the accuracy of automatic diagnosis was improved from 61.9% and 51.9% to 76.2% and 68.0%.The method is expected to provide an effectual method for the clinical automatic diagnosis of breast tissue disease." @default.
- W2392279436 created "2016-06-24" @default.
- W2392279436 creator A5031025871 @default.
- W2392279436 date "2013-01-01" @default.
- W2392279436 modified "2023-09-25" @default.
- W2392279436 title "An Optimization Algorithm of Automatic Diagnosis of Breast Tissues Based on Electrical Impedance Spectroscopy" @default.
- W2392279436 hasPublicationYear "2013" @default.
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