BREAST CANCER DIAGNOSIS BY ARTIFICIAL NEURAL NETWORKS (ANN’S)

Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/12737

Title:	BREAST CANCER DIAGNOSIS BY ARTIFICIAL NEURAL NETWORKS (ANN’S)
Authors:	Hassan, Ayat Mahmoud Ali, Roaa Mohammed Bilal, Shaza Babiker Supervised, -Eltahir Mohammed Hussein
Keywords:	BREAST CANCER ARTIFICIAL NEURAL NETWORKS NEURAL NETWORKS DIAGNOSIS
Issue Date:	1-Oct-2015
Publisher:	Sudan University of Sciences and Technology
Citation:	Hassan,Ayat Mahmoud.BREAST CANCER DIAGNOSIS BY ARTIFICIAL NEURAL NETWORKS (ANN’S)/Ayat Mahmoud Hassan,Roaa Mohammed Ali,Shaza Babiker Bilal;Eltahir Mohammed Hussein.-khartoum :Sudan University of Sciences and Technology,College of Engineering,2015.-45p:ill;28cm.-Bachelors search
Abstract:	Breast cancer is the second largest cause of cancer deaths among women. This project aim for early diagnosis of breast cancer and reduce the human diagnosis errorsthrough (ANN’s). Here we canstudy the performance of different Neural Network structures: Radial Basis Function(RBF), General Regression Neural Network (GRNN)and Back propagation NeuralNetwork(BPNN), are examined on the Wisconsin Breast Cancer Data (WBCD).The result demonstrated that; the BPNN is the best classification accuracy.
Description:	Bachelors search
URI:	http://repository.sustech.edu/handle/123456789/12737
Appears in Collections:	Bachelor of Engineering

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