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A Study on Firefly Algorithm for Breast Cancer Classification

  • Harikumar RajaguruEmail author
  • Sunil Kumar Prabhakar
Conference paper
Part of the Lecture Notes in Computational Vision and Biomechanics book series (LNCVB, volume 30)

Abstract

One of the most serious and prominent cancers which affect more women in this world is breast cancer. Various kinds of breast cancer have been reported in medical literature that significantly differ in their capability to spread to other tissues in the human body. Plenty of risk factors have been traced through research though the exact reasons of breast cancer are not yet fully understood. Advances in medicine and technology help to improve the quality of life for breast cancer patients. A lot of contribution especially in the area of artificial intelligence and data mining is done to aid the diagnosis and classification of breast cancer. In order to provide assistance to the doctors, oncologists, and clinicians, neural networks and other optimization techniques serves as a great boon. Here, in this paper, firefly algorithm is utilized effectively as a powerful tool for the analysis and classification of breast cancer. Results show that an average classification accuracy of 98.52% is obtained when firefly algorithm is used for the classification of breast cancer.

Keywords

Firefly algorithm Breast cancer Classification 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of ECEBannari Amman Institute of TechnologySathyamangalamIndia

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