UWB Rectangular Microstrip Patch Antenna Design in Matching Liquid and Evaluating the Classification Accuracy in Data Mining Using Random Forest Algorithm for Breast Cancer Detection with Microwave

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dc.authoridAVSAR AYDIN, Emine/0000-0002-5068-2957
dc.contributor.authorAydin, Emine Avsar
dc.contributor.authorKeles, Mumie Kaya
dc.date.accessioned2025-01-06T17:36:44Z
dc.date.available2025-01-06T17:36:44Z
dc.date.issued2019
dc.description.abstractThe most common type of cancer for a female is breast cancer in the world. Regular checks and effective-timely treatment are noteworthy parameters for patients' survival struggle . Against existing imaging methods, microwave imaging method has been considered more powerful and effective method by many researchers. In this paper, comprehensive design equations and parameters of rectangular microstrip patch antenna (RMPA) are given for microwave breast cancer detection. The layered breast model with a spherical tumor that was placed into the fibro-glandular layer was created by using CST Microwave Studio Software, and it was embedded in canola oil to decrease the distorted signals between the transmitting and receiving antennas. The RMPA has a wideband performance from 3 to 18GHz. The simulation results show that differences in the electric field and reflection coefficients might more efficiently give a possibility to assign the tumor in the breast model. In addition, in this study, the data obtained from these experiments are classified by using the random forest algorithm from the data mining methods. According to the classification result, the random forest algorithm can diagnose breast cancer by classifying the tumor as 94% accuracy.
dc.description.sponsorshipAdana Science and Technology University Scientific Research Projects Commission [18119003]
dc.description.sponsorshipThis research was partially supported by Adana Science and Technology University Scientific Research Projects Commission. Project number: 18119003.
dc.identifier.doi10.1007/s42835-019-00205-x
dc.identifier.endpage2136
dc.identifier.issn1975-0102
dc.identifier.issn2093-7423
dc.identifier.issue5
dc.identifier.scopus2-s2.0-85066904992
dc.identifier.scopusqualityQ2
dc.identifier.startpage2127
dc.identifier.urihttps://doi.org/10.1007/s42835-019-00205-x
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1984
dc.identifier.volume14
dc.identifier.wosWOS:000486900700032
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer Singapore Pte Ltd
dc.relation.ispartofJournal of Electrical Engineering & Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241211
dc.subjectBreast cancer detection
dc.subjectClassification
dc.subjectData mining
dc.subjectRandom forest algorithm
dc.subjectRectangular microstrip patch antenna
dc.titleUWB Rectangular Microstrip Patch Antenna Design in Matching Liquid and Evaluating the Classification Accuracy in Data Mining Using Random Forest Algorithm for Breast Cancer Detection with Microwave
dc.typeArticle

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