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Reseach Article

Prediction of Breast Cancer Risk Level with Risk Factors in Perspective to Bangladeshi Women using Data Mining

by Kawsar Ahmed, Md. Ahsan Habib, Tasnuba Jesmin, Md. Zamilur Rahman, Md. Badrul Alam Miah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 82 - Number 4
Year of Publication: 2013
Authors: Kawsar Ahmed, Md. Ahsan Habib, Tasnuba Jesmin, Md. Zamilur Rahman, Md. Badrul Alam Miah
10.5120/14107-2147

Kawsar Ahmed, Md. Ahsan Habib, Tasnuba Jesmin, Md. Zamilur Rahman, Md. Badrul Alam Miah . Prediction of Breast Cancer Risk Level with Risk Factors in Perspective to Bangladeshi Women using Data Mining. International Journal of Computer Applications. 82, 4 ( November 2013), 36-41. DOI=10.5120/14107-2147

@article{ 10.5120/14107-2147,
author = { Kawsar Ahmed, Md. Ahsan Habib, Tasnuba Jesmin, Md. Zamilur Rahman, Md. Badrul Alam Miah },
title = { Prediction of Breast Cancer Risk Level with Risk Factors in Perspective to Bangladeshi Women using Data Mining },
journal = { International Journal of Computer Applications },
issue_date = { November 2013 },
volume = { 82 },
number = { 4 },
month = { November },
year = { 2013 },
issn = { 0975-8887 },
pages = { 36-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume82/number4/14107-2147/ },
doi = { 10.5120/14107-2147 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:56:55.745955+05:30
%A Kawsar Ahmed
%A Md. Ahsan Habib
%A Tasnuba Jesmin
%A Md. Zamilur Rahman
%A Md. Badrul Alam Miah
%T Prediction of Breast Cancer Risk Level with Risk Factors in Perspective to Bangladeshi Women using Data Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 82
%N 4
%P 36-41
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The upgraded and modern medical technologies are the most challenging task to detect cancer and provide accurate treatment. In Bangladesh about two million women are affected by 2nd most occurring deathful breast cancer due to them and their family member's unconsciousness and poverty. It requires about $400-500 for proper diagnosis and treatment. Most of the Bangladeshi women are uneducated and feel shy with society or husband to go doctor for checking breast cancer. So it also will be a good achievement of this work to find breast cancer with more efficiency. Breast cancer depends on some risk factors that may help to detect breast cancer using multi-layered approach. In this work, at first it is collected 100 peoples' information which consist of both cancer and non-cancer information having missing or duplicate information. So pre-processing and K-means clustering methods are performed to separate relevant and non-relevant data to Breast Cancer. Then risk factors are ranked using WEKA tools and are assigned a score according to rank. Finally, it is implemented an application software using Lotus Notes to predict Breast Cancer risk level which is easier, effective, efficient, secured, cheap and time saving with some suggestions. This technique will contribute equal opportunity to the underdeveloped and developing countries to detect, diagnosis, and treatment of breast cancer.

References
  1. H. L. Story, R. R. Love, R. Salim, A. J. Roberto, J. L. Krieger, O. M. , "Improving Outcomes from Breast Cancer in a Low-Income Country: Lessons from Bangladesh", International Journal of Breast Cancer, 2012, pp. 1-9. Article ID 423562.
  2. M. Brown, S. Goldie, G. Draisma, J. Harford, J. Health service interventions for cancer control in developing countries in Disease Control Priorities in Developing Countries. Oxford University Press, 2006, vol. 2, pp. 569-90.
  3. World Cancer Research Fund. Available from: http://www. wcrf. org/cancer_facts/women-breast-cancer. php/. Accessed March 10, 2013.
  4. K. Ahmed, T. Jesmin, Md. Z. Rahman, "Early Prevention and Detection of Skin Cancer Risk Using Data Mining" International Journal of Computer Applications, 2013, vol. 62, pp. 1-6.
  5. K. Ahmed, Abdullah-Al-Emran, T. Jesmin, R. F. Mukti, Md. Z. Rahman, F. Akter, "Early Detection of Lung Cancer Risk Using Data Mining", Asian Pacific Journal of Cancer Prevention, 2013, vol. 14 pp. 595-98.
  6. T. Jesmin, K. Ahmed, Md. Z. Rahman, Md. B. A. Miah, "Brain Cancer Risk Prediction Tool Using Data Mining", International Journal of Computer Applications, 2013, vol. 61, pp. 22-27.
  7. K. Ahmed, T. Jesmin, U. Fatima, Md. M. , Abdullah-al-E. , Md. Z. Rahman, "Intelligent and Effective Diabetes Prediction System Using Data Mining Approach", ORIENTAL JOURNAL OF COMPUTER SCIENCE & TECHNOLOGY, 2012, vol. 5, pp. 215-21.
  8. Frawley, Piatetsky S. , "Knowledge Discovery in Databases: An Overview", the AAAI/MIT Press Menlo Park C. A.
  9. H. C. Koh, G. Tan, "Data Mining Applications in Healthcare" Journal of Healthcare Information Management, vol. 19, pp. 64-72.
  10. Z. Nouir, B. Sayrac, B. Fourestié, W. Tabbara, F. B. , "Generalization Capabilities Enhancement of a Learning System by Fuzzy Space Clustering" Journal of Communications, 2007, vol. 2, pp. 30-7.
  11. C. Ordonez, "Programming the K-Means Clustering Algorithm in SQL", in Proc. ACM Int'l Conf. Knowledge Discovery and Data Mining, 2004, pp. 823-8.
  12. Daniel B. K. , "Early Breast Cancer Detection Using Techniques other than Mammography", American Journal of Roentgenology, 1984, pp. 465-8.
  13. Medical Center University of Bonn, "Improving Methods for Breast Cancer Detection and Diagnosis", National Cancer Institute, 2003.
  14. S. V, S. C, W. L, Bourke A. , "New diagnostic techniques for breast cancer detection" US National Library of Medicine National Institutes of Health, 2008, vol. 4, pp. 501-13.
Index Terms

Computer Science
Information Sciences

Keywords

Breast cancer in Bangladesh Public health Data mining Risk factors of breast cancer WEKA toolkit Woman Health Conditions