Diagnosis of Pancreatic Cancer by Pattern Recognition Methods Using Gene Expression Profiles

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dc.contributor.authorArslan, Derya
dc.contributor.authorOzdemir, Merve Erkinay
dc.contributor.authorArslan, Mustafa Turan
dc.date.accessioned2024-09-18T20:25:18Z
dc.date.available2024-09-18T20:25:18Z
dc.date.issued2017
dc.departmentHatay Mustafa Kemal Üniversitesien_US
dc.description2017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEYen_US
dc.description.abstractPancreatic cancer is the fourth most common cause of cancer-related deaths across the globe and it is one of the most difficult cancer types to recognize early. Early diagnosis of pancreatic cancer is crucial to increase survival for patients. In this study, it was tried to be estimated that persons were pancreatic cancer or healthy using microarray gene expression profile. In accordance with this purpose, Anova method was used to reduce the size of high-dimensional pancreatic cancer gene expression profile and eliminate redundant features. Reducedsize pancreas cancer gene expression profiles were classified by k-nearest neighbor (k-NN) and artificial neural network (ANN) algorithms. The classification accuracy is %82.7 and 84.6% with k-NN, ANN respectively. The promising results indicate that pancreatic cancer can be diagnosed with high accuracy.en_US
dc.description.sponsorshipIEEE Turkey Sect,Anatolian Scien_US
dc.identifier.isbn978-1-5386-1880-6
dc.identifier.scopus2-s2.0-85039908680en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://hdl.handle.net/20.500.12483/10231
dc.identifier.wosWOS:000426868700167en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isotren_US
dc.publisherIeeeen_US
dc.relation.ispartof2017 International Artificial Intelligence and Data Processing Symposium (Idap)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGene expression profileen_US
dc.subjectpancreatic canceren_US
dc.subjectartificial neural networken_US
dc.subjectk-nearest neighboren_US
dc.titleDiagnosis of Pancreatic Cancer by Pattern Recognition Methods Using Gene Expression Profilesen_US
dc.typeConference Objecten_US

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