期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2019
卷号：10
期号：7
页码：106-111
DOI：10.14569/IJACSA.2019.0100716
出版社：Science and Information Society (SAI)
摘要：Cancer is the uncontrolled growth of abnormal cells in the body and is a major death cause nowadays. It is notable that cancer treatment is much easier in the initial stage rather than it outbreaks. DNA microarray based gene expression profiling has become efficient technique for cancer identification in early stage and a number of studies are available in this regard. Existing methods used different feature selection methods to select relevant genes and then employed distinct classifiers to identify cancer. This study considered information theoretic based minimum Redundancy Maximum Relevance (mRMR) method to select important genes and then employed artificial neural network (ANN) for cancer classification. Proposed mRMR-ANN method has been tested on a suite of benchmark datasets of various cancer. Experimental results revealed the proposed method as an effective method for cancer classification when performance compared with several related exiting methods.
