An Efficient Approach for Cancer Prediction Using Genomic Signal Processing

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Recent advances in bioinformatics and genomic signal processing have generated much interest due to the integration of theory and methods of signal processing with the global understanding of the functional genomics of organisms. In this paper, we propose a method to predict cancer based on the signal processing of the (Deoxyribo nucleic acid) DNA sequence. In the proposed method, entropy of the DNA sequence is found to predict cancer. For the analysis, we use DNA sequences obtained from National Centre for Biotechnology information (NCBI). Evaluation metrics parameters of Sensitivity, Specificity and Accuracy are found out and compared with the existing methods. From the results, it is clear that our method has attained better evaluation metrics parameters. It gave 86.36% accuracy, 90.9% specificity and 81.81% Sensitivity. When compared to literature, our method produces better results
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Cancer Prediction; DNA Sequences; Entropy; Genomic Signal Processing

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