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dc.contributor.authorAl-Barzinji, Shokhan M.-
dc.date.accessioned2022-10-20T16:29:03Z-
dc.date.available2022-10-20T16:29:03Z-
dc.date.issued2018-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/4038-
dc.description.abstractLung cancer (LC) is the leading cause of cancer-related deaths, both in women and among men. Yearly, LC kills more people than other cancers such as colon cancer, prostate cancer, and lymphoma and breast cancer, with 2.8 million deaths in 2017. To analyze any disease characteristics, a data mining is used for decision support process, specify the disease with its details. Data mining techniques are the amount of actual data are used to analyze these data to predict wholesome data to support a decision-making in a problem-solving. In this paper, used a data mining techniques, hybrid model Radial Basis Function - Neural Network (RBF-NN) and Genetic Algorithms (GA) to support different healthcare fields and adopted a correct decision about the diagnosis of LC disease and specify the risk factors for this disease to support decision process. The results demonstrate that the prediction accuracy of LC through the hybrid method is about 94%.en_US
dc.language.isoenen_US
dc.publisherIraqi Journal of Information Technologyen_US
dc.relation.ispartofseries8;4-
dc.subjectRadial Basis Function Neural Network (RBF-NN)en_US
dc.subjectDecision Support (DS)en_US
dc.subjectData Miningen_US
dc.subjectGenetic Algorithm (GA)en_US
dc.titleDiagnosis Lung Cancer Disease Using Machine Learning Techniquesen_US
dc.typeArticleen_US
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