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Breast Cancer Diagnostic System using Hierarchical Learning Vector Quantization

Published on February 2013 by R. R. Janghel, Ritu Tiwari, Anupam Shukla
National Seminar on Application of Artificial Intelligence in Life Sciences 2013
Foundation of Computer Science USA
NSAAILS - Number 1
February 2013
Authors: R. R. Janghel, Ritu Tiwari, Anupam Shukla
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R. R. Janghel, Ritu Tiwari, Anupam Shukla . Breast Cancer Diagnostic System using Hierarchical Learning Vector Quantization. National Seminar on Application of Artificial Intelligence in Life Sciences 2013. NSAAILS, 1 (February 2013), 14-18.

@article{
author = { R. R. Janghel, Ritu Tiwari, Anupam Shukla },
title = { Breast Cancer Diagnostic System using Hierarchical Learning Vector Quantization },
journal = { National Seminar on Application of Artificial Intelligence in Life Sciences 2013 },
issue_date = { February 2013 },
volume = { NSAAILS },
number = { 1 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 14-18 },
numpages = 5,
url = { /proceedings/nsaails/number1/10379-1003/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Seminar on Application of Artificial Intelligence in Life Sciences 2013
%A R. R. Janghel
%A Ritu Tiwari
%A Anupam Shukla
%T Breast Cancer Diagnostic System using Hierarchical Learning Vector Quantization
%J National Seminar on Application of Artificial Intelligence in Life Sciences 2013
%@ 0975-8887
%V NSAAILS
%N 1
%P 14-18
%D 2013
%I International Journal of Computer Applications
Abstract

Breast cancer has become a common mortality factor in the world. Lesser availability of diagnostic facilities along with large time requirements in manual diagnosis emphasize on automatic diagnosis for early diagnosis of the disease. In this paper a computerized breast cancer diagnosis prototype has been developed to reduce the time taken and indirectly reducing the probability of death. The paper presents Hierarchical Learning Vector Quantization (HLVQ) as a classifier for the diagnosis. Hierarchical LVQ networks consist of multiple LVQ networks assembled in different level or cascade architecture. In this research two stage of LVQ network is used on WDBC datasets. The first level of LVQ reduces the feature space which is further worked over by the second stage for computing the output. The experiments confirm an effective detection of the disease by use of multiple networks. A comparative study of work carried in the field of breast cancer diagnosis using different ANN algorithm is also done.

References
  1. World Health Organization International Agency for Research on Cancer (June 2003). "World Cancer Report". http://www. iarc. fr/en/Publications/PDFs-online/World-Cancer-Report/World-Cancer-Report. Retrieved 2009-03-26.
  2. World Health Organization (February 2006). "Fact sheet No. 297: Cancer". http://www. who. int/mediacentre/factsheets/fs297/en/index. html. Retrieved 2009-03-26.
  3. Jemal, A. ; Siegel, R. ; Ward, E. ; Hao, Y. ; and "Cancer Statistics,". CA Cancer Journal for Clinicians, 59, 225-249, 2009.
  4. Strax, P. , "Make Sure that You Do Not Have Breast Cancer," St. Martin's, NY, 1989.
  5. O. L. Mangasarian and W. H. Wolberg: "Cancer diagnosis via linear programming", SIAM News, Volume 23, Number 5, September 1990, pp 1 & 18.
  6. Mangasarian, O. L. , Street, W. N. , and Wolberg, W. H. (1995). Breast cancer diagnosis and prognosis via linear programming. Operations Research, 43(4):570-577.
  7. Wolberg, W. H. , Street, W. N. , and Mangasarian, O. L. (1994). Machine learning techniques to diagnose breast cancer from image-processed nuclear features of fine needle aspirates. Cancer Letters, 77:163-171.
  8. "Cancer Research Statistics: May 2009", 2009, Imperial Cancer Research Campaign, U. K.
  9. Shukla, A. ; Tiwari, R. ; Kaur, P. ; "Knowledge Based Approach for Diagnosis of Breast Cancer", Advance Computing Conference, 2009. IACC 2009. IEEE International, Page(s):6 – 12, 6-7 March 2009.
  10. Janghel R. R , Shukla Anupam, Kala Rahul and Tiwari Ritu "Diagnosis of Breast Cancer by Modular Evolutionary Neural Networks at International Journal of Biomedical Engineering and Technology, Inderscience Enterprises Ltd , Vol. x, No. x, xxxx , pp 1-18, 2010.
  11. Janghel R. R , Shukla Anupam, Kala Rahul and Tiwari Ritu, Intelligent Diagnostic System for the diagnosis and prognosis of Breast Cancer using ANN, Journal of Computing, Volume 2, Issue 12 (Accepted).
  12. Janghel R. R , Shukla Anupam, Kala Rahul and Tiwari Ritu,International Journal of Information Systems and Social Change (IJISSC) (Accepted).
  13. Janghel R. R , Shukla anupam,Tiwari Ritu and Kaur Prabhdeep, Diagnosis of Thyroid Disorders using Artificial Neural Networks on 2009 IEEE International Advance Computing Conference (IACC 2009),Patiala, India, 6–7March 2009,pp:2722-2726.
  14. Janghel R. R , Shukla anupam,Tiwari Ritu and Pritesh Tiwari , "Clinical Decision support system for fetal Delivery using Artificial Neural Network"2009 (NISS) IEEE International Conference on New Trends in Information and Service Science, June 30 – July 2, 2009, Beijing, China,pp:1070-1075.
  15. Janghel R. R , Shukla Anupam and Tiwari Ritu " Decision Support System for Fetal Delivery using Soft Computing Techniques" (2nd ICIS), 2009 International Conference on Interaction Sciences: Information Technology, Culture and Human, IEEE CPS series ,24-26 November, 2009 - Seoul, Korea, pp: 1514-1519.
  16. Janghel R. R, Shukla Anupam and Tiwari Ritu "Intelligent Decision Support System for Breast Cancer" International Conference on Swarm Intelligence (ICSI 2010) Beijing, China, 12-15 June 2010, ICSI 2010, Part II, LNCS 6146, pp. 351–358, 2010. Springer-Verlag Berlin Heidelberg 2010.
  17. Janghel R. R , Shukla Anupam and Tiwari Ritu "Breast Cancer Diagnosis using Artificial Neural Network Models" (3nd ICIS), 2010 3rd International Conference on Information Sciences and Interaction Sciences, IEEE Explore , June 23-25, 2010, Chengdu, China (Accepted).
  18. Janghel R. R , Shukla Anupam, Tiwari Ritu and Rahul Kala Breast Cancer Diagnostic System using Symbiotic Adaptive Neuro-evolution (SANE), The lnternational Conference of Soft Computing and Pattern Recognition(SoCPaR2 010 ), IEEE Explore, Dec 07-10, 2010 ,France.
Index Terms

Computer Science
Information Sciences

Keywords

Breast Cancer Neural Networks Diagnosis Learning Vector Quantization Hierarchical Lvq