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Novel modelling of clustering for enhanced classification performance on gene expression data
2020
International Journal of Electrical and Computer Engineering (IJECE)
Gene expression data is popularized for its capability to disclose various disease conditions. However, the conventional procedure to extract gene expression data itself incorporates various artifacts that offer challenges in diagnosis a complex disease indication and classification like cancer. Review of existing research approaches indicates that classification approaches are few to proven to be standard with respect to higher accuracy and applicable to gene expression data apart from
doi:10.11591/ijece.v10i2.pp2060-2068
fatcat:2f4eugmnnnctlhtkfp6wrpbk6y