Downloads: 118 | Views: 129
Research Paper | Computers in Biology and Medicine | India | Volume 8 Issue 7, July 2019
A Model for Classification of Wisconsin Breast Cancer Datasets using Principal Component Analysis and Back-Propagation Neural Network
Shweta Saxena  | Manasi Gyanchandani
Abstract: Nowadays, the second leading reason of death (due to cancer) among females is breast cancer. Early detection of this disease can significantly enhance the probabilities of long-term survival of breast cancer patients. This paper proposes a computer-aided-diagnosis model for Wisconsin Breast Cancer (WBC) datasets using Back-Propagation Neural Network (BPNN). The data pre-processing technique named principal component analysis (PCA) is proposed as a feature reduction and transformation method to improve the accuracy of BPNN.
Keywords: Breast Cancer, Computer-Aided-Diagnosis, Principal Component Analysis, Back-Propagation Neural Network
Edition: Volume 8 Issue 7, July 2019,
Pages: 1324 - 1327
Similar Articles with Keyword 'Breast Cancer'
Research Paper, Computers in Biology and Medicine, Turkey, Volume 8 Issue 6, June 2019Pages: 885 - 891
Predicting Breast Cancer Using Gradient Boosting Machine
Sahr Imad Abed
Research Paper, Computers in Biology and Medicine, Iraq, Volume 7 Issue 2, February 2018Pages: 1023 - 1032
Breast Cancer Diagnosis System Based on Nuclei Cells Localization of Fine Needle Biopsies Images
Ali Fawzi Mohammed Ali | Mehdi G. Duaimi