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• W830216635 abstract "Cardiotocographic (CTG) monitoring is a method of assessing fetal state. Since visual analysis of CTG signal is difficult, methods of automated qualitative fetal state evaluation on the basis of the quantitative description of the signal are applied. The appropriate selection of learning data influences the quality of the fetal state assessment with computational intelligence methods. In the presented work we examined three different feature selection procedures based on: principal components analysis, receiver operating characteristics and guidelines of International Federation of Gynecology and Obstetrics. To investigate their influence on the fetal state assessment quality the benchmark SisPortor dataset and the Lagrangian support vector machine were used." @default.
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• W830216635 date "2014-01-01" @default.
• W830216635 modified "2023-10-16" @default.
• W830216635 title "The influence of cardiotocogram signal feature selection method on fetal state assessment efficacy" @default.
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• W830216635 hasPublicationYear "2014" @default.
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