Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/4038
Title: Diagnosis Lung Cancer Disease Using Machine Learning Techniques
Authors: Al-Barzinji, Shokhan M.
Keywords: Radial Basis Function Neural Network (RBF-NN)
Decision Support (DS)
Data Mining
Genetic Algorithm (GA)
Issue Date: 2018
Publisher: Iraqi Journal of Information Technology
Series/Report no.: 8;4
Abstract: Lung 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%.
URI: http://localhost:8080/xmlui/handle/123456789/4038
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