BREAST CANCER DIAGONOSIS IN ANALYSIS OF BRCA GENE USING MACHINE LEARNING ALGORITHMS

Authors

  • J. Sumitha
  • T. Devi

Keywords:

Confusion matrix, DCKSVM, Identification of BRCA gene, HRBFNN, Sequential model.

Abstract

Worldwide, the breast cancer is the second leading cancer type which leads to death among women. Breast
cancer exists due to the mutation happens in the normal growth of Breast Cancer Gene (BRCA) under certain
circumstances. In this paper, we proposed the existing machine learning algorithms for finding the disease – causing
BRCA gene. These existing machine learning algorithms are compared with each other to determine the efficiency
in detecting the diseases from gene expression value. The results proved that the Hybrid Radial Bias Neural
Network (HRBFNN) performs better than Divide and Conquer

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Published

2016-12-25

How to Cite

J. Sumitha, & T. Devi. (2016). BREAST CANCER DIAGONOSIS IN ANALYSIS OF BRCA GENE USING MACHINE LEARNING ALGORITHMS. Pakistan Journal of Biotechnology, 13(4), 231–235. Retrieved from https://pjbt.org/index.php/pjbt/article/view/10

Issue

Section

Research Articles