Titlebook: Computational Intelligence Processing in Medical Diagnosis; Manfred Schmitt,Horia-Nicolai Teodorescu,Lakhmi C. Book 2002 Springer-Verlag B

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Genetic Algorithms for Feature Selection in Computer-Aided Diagnosis, CAD can improve the accuracy of breast cancer detection and characterization by radiologists on mammograms. In this chapter, we discuss an important step — feature selection — in classifier design for CAD algorithms. Feature selection reduces the dimensionality of an available feature space and is

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Generalizations and Extensions,cutoff was applied to the 100 records of the test file. ROC analysis revealed that a cutoff of 0.30 maximized specificity while maintaining perfect sensitivity in the cutoff determination file. The cutoff of 0.30 also maintained perfect sensitivity in the test file, while the trained network made ou

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Computational Intelligence Processing in Medical Diagnosis

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Neural Network Predictions of Significant Coronary Artery Stenosis in Women,cutoff was applied to the 100 records of the test file. ROC analysis revealed that a cutoff of 0.30 maximized specificity while maintaining perfect sensitivity in the cutoff determination file. The cutoff of 0.30 also maintained perfect sensitivity in the test file, while the trained network made ou

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Genetic Algorithms for Feature Selection in Computer-Aided Diagnosis,xamples illustrate the design of a fitness function for optimizing classification accuracy in terms of the receiver operating characteristics of the classifier, the dependence of GA performance on its evolution parameters, and the design of a fitness function tailored to a specific classification ta