CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Early Detection and Prevention of Cancer using Data Mining Techniques

by P. Ramachandran, N. Girija, T. Bhuvaneswari
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 97 - Number 13
Year of Publication: 2014
Authors: P. Ramachandran, N. Girija, T. Bhuvaneswari
10.5120/17069-7492

P. Ramachandran, N. Girija, T. Bhuvaneswari . Early Detection and Prevention of Cancer using Data Mining Techniques. International Journal of Computer Applications. 97, 13 ( July 2014), 48-53. DOI=10.5120/17069-7492

@article{ 10.5120/17069-7492,
author = { P. Ramachandran, N. Girija, T. Bhuvaneswari },
title = { Early Detection and Prevention of Cancer using Data Mining Techniques },
journal = { International Journal of Computer Applications },
issue_date = { July 2014 },
volume = { 97 },
number = { 13 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 48-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume97/number13/17069-7492/ },
doi = { 10.5120/17069-7492 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:24:02.597666+05:30
%A P. Ramachandran
%A N. Girija
%A T. Bhuvaneswari
%T Early Detection and Prevention of Cancer using Data Mining Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 97
%N 13
%P 48-53
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cancer is one of the leading causes of death worldwide. Early detection and prevention of cancer plays a very important role in reducing deaths caused by cancer. Identification of genetic and environmental factors is very important in developing novel methods to detect and prevent cancer. Therefore a novel multi layered method combining clustering and decision tree techniques to build a cancer risk prediction system is proposed here which predicts lung, breast, oral, cervix, stomach and blood cancers and is also user friendly, time and cost saving. This research uses data mining technology such as classification, clustering and prediction to identify potential cancer patients. The gathered data is preprocessed, fed into the database and classified to yield significant patterns using decision tree algorithm. Then the data is clustered using K- means clustering algorithm to separate cancer and non cancer patient data. Further the cancer cluster is subdivided into six clusters. Finally a prediction system is developed to analyze risk levels which help in prognosis. This research helps in detection of a person's predisposition for cancer before going for clinical and lab tests which is cost and time consuming.

References
  1. Ada and Rajneet Kaur "Using Some Data Mining Techniques to Predict the Survival Year of Lung Cancer Patient" International Journal of Computer Science and Mobile Computing, IJCSMC, Vol. 2, Issue. 4, April 2013, pg. 1 – 6, ISSN 2320–088X
  2. V. Krishnaiah "Diagnosis of Lung Cancer Prediction System Using Data Mining Classification Techniques" International Journal of Computer Science and Information Technologies, Vol. 4 (1) 2013, 39 – 45 www. ijcsit. Com ISSN: 0975-9646.
  3. Charles Edeki "Comparative Study of Data Mining and Statistical Learning Techniques for Prediction of Cancer Survivability" Mediterranean journal of Social Sciences Vol 3 (14) November 2012, ISSN: 2039-9340.
  4. A. Sahar "Predicting the Serverity of Breast Masses with Data Mining Methods" International Journal of Computer Science Issues, Vol. 10, Issues 2, No 2, March 2013 ISSN (Print):1694-0814| ISSN (Online):1694-0784 www. IJCSI. org
  5. Rajashree Dash "A hybridized K-means clustering approach for high dimensional dataset" International Journal of Engineering, Science and Technology Vol. 2, No. 2, 2010, pp. 59-66
  6. Ritu Chauhan "Data clustering method for Discovering clusters in spatial cancer databases" International Journal of Computer Applications (0975-8887) Volume 10-No. 6, November 2010.
  7. Dechang Chen "Developing Prognostic Systems of Cancer Patients by Ensemble Clustering" Hindawi publishing corporation, Journal of Biomedicine and Biotechnology Volume 2009, Article Id 632786.
  8. S M Halawani "A study of digital mammograms by using clustering algorithms" Journal of Scientific & Industrial Research Vol. 71, September 2012, pp. 594-600.
  9. Zakaria Suliman zubi "Improves Treatment Programs of Lung Cancer using Data Mining Techniques" Journal of Software Engineering and Applications, February 2014, 7, 69-77
  10. Labeed K Abdulgafoor "Detection of Brain Tumor using Modified K-Means Algorithm and SVM" International Journal of Computer Applications (0975 – 8887) National Conference on Recent Trends in Computer Applications NCRTCA 2013
  11. Alaa. M. Elsayad "Diagnosis of Breast Cancer using Decision Tree Models and SVM" International Journal of Computer Applications (0975 – 8887) Volume 83 – No 5, December 2013
  12. Neelamadhab Padhy "The Survey of Data Mining Applications and Feature Scope" Asian Journal of Computer Science and Information Technology 2:4(2012) 68-77 ISSN 2249-5126
  13. S. Santhosh Kumar "Development of an Efficient Clustering Technique for Colon Dataset" International Journal of Engineering and Innovative Technology" Volume 1, Issue 5, May 2012 ISSN: 2277-3754
  14. Rafaqat Alam Khan "Classification and Regression Analysis of the Prognostic Breast Cancer using Generation Optimizing Algorithms" International Journal of Computer Applications (0975-8887) Volume 68- No. 25, April 2013
  15. K. Kalaivani "Childhood Cancer-a Hospital based study using Decision Tree Techniques" Journal of Computer Science 7(12): 1819-1823, 2011 ISSN: 1549-3636
  16. Boris Milovic "Prediction and Decision Making in Health Care using Data Mining" International Journal of Public Health Science Vol. 1, No. 2, December 2012, pp. 69-78 ISSN: 2252-8806
  17. T. Revathi "A Survey on Data Mining Using Clustering Techniques" International Journal of Scientific & Engineering Research Http://Www. Ijser. Org, Volume 4, Issue 1, January-2013, Issn 2229-5518
  18. Shomona Gracia Jacob "Data Mining in Clinical Data Sets: A. Review" International Journals of Applied Information System (IJAIS) - ISSN: 2249-0868 Foundation of Computer Science FCS, New York, USA, Volume 4-No. 6, December 2012-www. ijais. org
  19. G. Rajkumar " Intelligent Pattern Mining and Data Clustering for Pattern Cluster Analysis using Cancer Data" International journal of Engineering Science and Technology Vol. 2(12), 2010, ISSN: 7459-7469.
  20. M. Durairaj "Data Mining Applications in Healthcare Sector: A Study" International journal of Scientific & Technology Research, Volume 2, Issue 10, October 2013, ISSN: 2277-8616
  21. Vikas Chaurasia "Data Mining Techniques: To Predict and Resolve Breast Cancer Survivability" International journal of Computer Science and Mobile Computing (IJCSMC), Vol. 3, Issue. 1, January 2014, pg. 10-22, ISSN: 2320-088X
  22. T. Sridevi "An Intelligent Classifier for Breast Cancer Diagnosis based on K-Means Clustering and Rough Set" International Journal of Computer Applications (0975 – 8887) Volume 85 – No 11, January 2014
  23. Reeti Yadav "Chemotheraphy Prediction of Cancer Patient by Using Data Mining Techniques" International Journal of Computer Applications (0975-8887), Volume 76-No. 10, August 2013
  24. K. Balachandran "Classifiers based Approach for Pre-Diagnosis of Lung Cancer Disease" International Journal of Computer Applications® (IJCA) (0975 – 8887)
Index Terms

Computer Science
Information Sciences

Keywords

Decision Tree k-means Prediction Prognosis Risk Levels

Powered by PhDFocusTM