A novel SVM-ID3 Hybrid Feature Selection Method to Build a Disease Model for Melanoma using Integrated Genotyping and Phenotype Data from dbGaP

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dc.authoridAYDIN SON, YESIM/0000-0002-8118-4272
dc.authoridYucebas, Sait Can/0000-0002-1030-3545
dc.contributor.authorSon, Yesim Aydin
dc.contributor.authorYucebas, Sait Can
dc.date.accessioned2025-01-27T20:31:56Z
dc.date.available2025-01-27T20:31:56Z
dc.date.issued2014
dc.departmentÇanakkale Onsekiz Mart Üniversitesi
dc.description25th European Medical Informatics Conference (MIE) -- AUG 31-SEP 03, 2014 -- Istanbul, TURKEY
dc.description.abstractThe relations between Single Nucleotide Polymorphism (SNP) and complex diseases are likely to be non-linear and require analysis of the high dimensional data. Previous studies in the field mostly focus on genotyping and effects of various phenotypes are not considered. To fill this gap a hybrid feature selection model of support vector machine and decision tree has been designed. The designed method is tested on melanoma. We were able to select phenotypic features such as moles and dysplastic nevi, and SNPs those maps to specific genes such as CAMK1D. The performance results of the proposed hybrid model, on melanoma dataset are 79.07% of sensitivity and 0.81 of area under ROC curve.
dc.identifier.doi10.3233/978-1-61499-432-9-501
dc.identifier.endpage505
dc.identifier.isbn978-1-61499-432-9
dc.identifier.isbn978-1-61499-431-2
dc.identifier.issn0926-9630
dc.identifier.issn1879-8365
dc.identifier.pmid25160235
dc.identifier.scopus2-s2.0-84929518399
dc.identifier.scopusqualityQ3
dc.identifier.startpage501
dc.identifier.urihttps://doi.org/10.3233/978-1-61499-432-9-501
dc.identifier.urihttps://hdl.handle.net/20.500.12428/23309
dc.identifier.volume205
dc.identifier.wosWOS:000454226100099
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherIos Press
dc.relation.ispartofE-Health - For Continuity of Care
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WoS_20250125
dc.subjectGenome Wide Association Studies (GWAS)
dc.subjectSingle Nucleotide Polymorphism (SNP)
dc.subjectData Mining
dc.subjectSupport Vector Machines (SVM)
dc.subjectDecision Trees
dc.subjectHybrid Models
dc.titleA novel SVM-ID3 Hybrid Feature Selection Method to Build a Disease Model for Melanoma using Integrated Genotyping and Phenotype Data from dbGaP
dc.typeConference Object

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