Matches in SemOpenAlex for { <https://semopenalex.org/work/W2045262022> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2045262022 endingPage "8315" @default.
- W2045262022 startingPage "8311" @default.
- W2045262022 abstract "In this paper, an automatic diagnosis system for diabetes on Linear Discriminant Analysis (LDA) and Morlet Wavelet Support Vector Machine Classifier: LDA–MWSVM is introduced. The structure of this automatic system based on LDA-MWSVM for the diagnosis of diabetes is composed of three stages: The feature extraction and feature reduction stage by using the Linear Discriminant Analysis (LDA) method and the classification stage by using Morlet Wavelet Support Vector Machine (MWSVM) classifier stage. The Linear Discriminant Analysis (LDA) is used to separate features variables between healthy and patient (diabetes) data in the first stage. The healthy and patient (diabetes) features obtained in the first stage are given to inputs of the MWSVM classifier in the second stage. Finally, in the third stage, the correct diagnosis performance of this automatic system based on LDA–MWSVM for the diagnosis of diabetes is calculated by using sensitivity and specificity analysis, classification accuracy, and confusion matrix, respectively. The classification accuracy of this system was obtained at about 89.74%." @default.
- W2045262022 created "2016-06-24" @default.
- W2045262022 creator A5071940990 @default.
- W2045262022 creator A5089519097 @default.
- W2045262022 date "2011-07-01" @default.
- W2045262022 modified "2023-10-17" @default.
- W2045262022 title "An automatic diabetes diagnosis system based on LDA-Wavelet Support Vector Machine Classifier" @default.
- W2045262022 cites W1519344613 @default.
- W2045262022 cites W1596717185 @default.
- W2045262022 cites W1817561967 @default.
- W2045262022 cites W1969109407 @default.
- W2045262022 cites W1982934478 @default.
- W2045262022 cites W1992006167 @default.
- W2045262022 cites W2011937074 @default.
- W2045262022 cites W2016979930 @default.
- W2045262022 cites W2019207321 @default.
- W2045262022 cites W2031030653 @default.
- W2045262022 cites W2042031583 @default.
- W2045262022 cites W2046650367 @default.
- W2045262022 cites W2054931700 @default.
- W2045262022 cites W2063752917 @default.
- W2045262022 cites W2078351515 @default.
- W2045262022 cites W2162642281 @default.
- W2045262022 cites W4239510810 @default.
- W2045262022 doi "https://doi.org/10.1016/j.eswa.2011.01.017" @default.
- W2045262022 hasPublicationYear "2011" @default.
- W2045262022 type Work @default.
- W2045262022 sameAs 2045262022 @default.
- W2045262022 citedByCount "89" @default.
- W2045262022 countsByYear W20452620222012 @default.
- W2045262022 countsByYear W20452620222013 @default.
- W2045262022 countsByYear W20452620222014 @default.
- W2045262022 countsByYear W20452620222015 @default.
- W2045262022 countsByYear W20452620222016 @default.
- W2045262022 countsByYear W20452620222017 @default.
- W2045262022 countsByYear W20452620222018 @default.
- W2045262022 countsByYear W20452620222019 @default.
- W2045262022 countsByYear W20452620222020 @default.
- W2045262022 countsByYear W20452620222021 @default.
- W2045262022 countsByYear W20452620222022 @default.
- W2045262022 countsByYear W20452620222023 @default.
- W2045262022 crossrefType "journal-article" @default.
- W2045262022 hasAuthorship W2045262022A5071940990 @default.
- W2045262022 hasAuthorship W2045262022A5089519097 @default.
- W2045262022 hasConcept C12267149 @default.
- W2045262022 hasConcept C138602881 @default.
- W2045262022 hasConcept C139532973 @default.
- W2045262022 hasConcept C153180895 @default.
- W2045262022 hasConcept C154945302 @default.
- W2045262022 hasConcept C181367576 @default.
- W2045262022 hasConcept C196216189 @default.
- W2045262022 hasConcept C2778280487 @default.
- W2045262022 hasConcept C31510193 @default.
- W2045262022 hasConcept C41008148 @default.
- W2045262022 hasConcept C46286280 @default.
- W2045262022 hasConcept C47432892 @default.
- W2045262022 hasConcept C52620605 @default.
- W2045262022 hasConcept C52622490 @default.
- W2045262022 hasConcept C69738355 @default.
- W2045262022 hasConcept C95623464 @default.
- W2045262022 hasConceptScore W2045262022C12267149 @default.
- W2045262022 hasConceptScore W2045262022C138602881 @default.
- W2045262022 hasConceptScore W2045262022C139532973 @default.
- W2045262022 hasConceptScore W2045262022C153180895 @default.
- W2045262022 hasConceptScore W2045262022C154945302 @default.
- W2045262022 hasConceptScore W2045262022C181367576 @default.
- W2045262022 hasConceptScore W2045262022C196216189 @default.
- W2045262022 hasConceptScore W2045262022C2778280487 @default.
- W2045262022 hasConceptScore W2045262022C31510193 @default.
- W2045262022 hasConceptScore W2045262022C41008148 @default.
- W2045262022 hasConceptScore W2045262022C46286280 @default.
- W2045262022 hasConceptScore W2045262022C47432892 @default.
- W2045262022 hasConceptScore W2045262022C52620605 @default.
- W2045262022 hasConceptScore W2045262022C52622490 @default.
- W2045262022 hasConceptScore W2045262022C69738355 @default.
- W2045262022 hasConceptScore W2045262022C95623464 @default.
- W2045262022 hasIssue "7" @default.
- W2045262022 hasLocation W20452620221 @default.
- W2045262022 hasOpenAccess W2045262022 @default.
- W2045262022 hasPrimaryLocation W20452620221 @default.
- W2045262022 hasRelatedWork W1965671931 @default.
- W2045262022 hasRelatedWork W2107265013 @default.
- W2045262022 hasRelatedWork W2116239864 @default.
- W2045262022 hasRelatedWork W2143240582 @default.
- W2045262022 hasRelatedWork W2347931439 @default.
- W2045262022 hasRelatedWork W2357758792 @default.
- W2045262022 hasRelatedWork W2513386338 @default.
- W2045262022 hasRelatedWork W2903240209 @default.
- W2045262022 hasRelatedWork W2948950091 @default.
- W2045262022 hasRelatedWork W4300889318 @default.
- W2045262022 hasVolume "38" @default.
- W2045262022 isParatext "false" @default.
- W2045262022 isRetracted "false" @default.
- W2045262022 magId "2045262022" @default.
- W2045262022 workType "article" @default.