A Comparative Study between Artificial Neural Network Performance and Adaptive Neuro-fuzzy Inference Systems in Breast Cancer Diagnosis Depending On Structural Features
published by Tishreen University
in 2017
in
and research's language is
العربية
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Abstract in English
This research aims to produce a diagnosis system for breast cancer by using Neural
Network depending on Back Propagation algorithm(BPNN) and Adaptive Neuro Fuzzy
Inference System ‘ANFIS’, the both of studies was done using structural features of
biopsies in “Wisconson Breast Cancer “data base.
In the end a comparison was made between the two studies of malignant- benign
classification of breast masses of breast cancer which has accuracy 95,95% with BPNN
and 91.9% with ANFIS system, this results can be consider very important if they
compared with researches depending on image features that obtained of various devises
like mammography, magnetic resonance.
References used
Ebrahim Edriss Ebrahim Ali, Wu Zhi Feng. Breast Cancer Classification using Support Vector Machine and Neural Network. International Journal of Science and Research (IJSR). Vol.5 No. 3, 2016, 1-6
K. A. Mohamed Junaid. Classification Using Two Layer Neural Network Back Propagation Algorithm. Circuits and Systems, Vol.1, No.7, 2016, 1207-1212
Htet Thazin, Tike Thein, Khin Mo. AN APPROACH FOR BREAST CANCER DIAGNOSIS CLASSIFICATION USING NEURAL NETWORK. Advanced Computing: An International Journal (ACIJ), Vol.6, No.1, 2015, 1-11