Cancer Classification from DNA Microarray Data using mRMR and Artificial Neural Network

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.

@article{Akhand2019,
  title     = {Cancer Classification from DNA Microarray Data using mRMR and Artificial Neural Network},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {10},
  number    = {7},
  year      = {2019},
  publisher = {The Science and Information Organization},
  author    = {M A H Akhand and Md. Asaduzzaman Miah and Mir Hussain Kabir and M. M. Hafizur Rahman},
  doi       = {10.14569/IJACSA.2019.0100716},
  url       = {https://doi.org/10.14569/IJACSA.2019.0100716}
}