DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-6, Issue-1 ( Jan, 2018 ) | |||||||||
Paper Title |
Approach for Classification of Breast Cancer: State-of-The-Art, Future Challenges and Research Direction | |||||||||
Author Name |
Rasha Attallah, Amirrudin Kamsin, Maizatul Akmar Ismail | |||||||||
Affilition |
[email protected], [email protected], [email protected] | |||||||||
Pages |
37-41 | |||||||||
Abstract |
Breast cancer is one of the most common type of cancer leading to death the women. Cancer grows due to uncontrolled increase of the cells in the breast and spreads gradually throughout the whole body resulting in death. The specialist said to reduce the death rate from breast cancer need to detect early an d diagnosis the diseases effectively . This survey paper aims at determining the current state of art in breast cancer detection and limitations of existing techniques. The survey reveals that various approaches have been proposed based on fuzzy logic, deep learning, neural network and other similar approaches which helping specialist in breast cancer to detect and prevent this disease. The comparison between existing approaches was done based on three main evaluation parameters i.e., accuracy, sensitivity and specificity along with data sets used. Index Terms—Breast Cancer, Fuzzy System, Deep learning, Mammogram, Neural network. | |||||||||
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