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Reseach Article

A Survey on Data Mining Techniques in the Medicative Field

by Chinky Gera, Kirti Joshi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 113 - Number 13
Year of Publication: 2015
Authors: Chinky Gera, Kirti Joshi
10.5120/19888-1926

Chinky Gera, Kirti Joshi . A Survey on Data Mining Techniques in the Medicative Field. International Journal of Computer Applications. 113, 13 ( March 2015), 32-35. DOI=10.5120/19888-1926

@article{ 10.5120/19888-1926,
author = { Chinky Gera, Kirti Joshi },
title = { A Survey on Data Mining Techniques in the Medicative Field },
journal = { International Journal of Computer Applications },
issue_date = { March 2015 },
volume = { 113 },
number = { 13 },
month = { March },
year = { 2015 },
issn = { 0975-8887 },
pages = { 32-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume113/number13/19888-1926/ },
doi = { 10.5120/19888-1926 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:50:52.139954+05:30
%A Chinky Gera
%A Kirti Joshi
%T A Survey on Data Mining Techniques in the Medicative Field
%J International Journal of Computer Applications
%@ 0975-8887
%V 113
%N 13
%P 32-35
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining is the process of releasing concealed information from a large set of database and it can help researchers gain both narrative and deep insights of exceptional understanding of large biomedical datasets. Data mining can exhibit new biomedical and healthcare knowledge for clinical decision making. Medical assessment is very important but complicated problem that should be performed efficiently and accurately. The goal of this paper is to discuss the research contributions of data mining to solve the complex problem of Medical diagnosis prediction. This paper also reviews the various techniques along with their pros and cons. Among various data mining techniques, evaluation of classification is widely adopted for supporting medical diagnostic decisions.

References
  1. Chaurasia V. et al. Mining Approaches to Detect Heart Diseases, International Journal of Advanced Computer Science and Information Technology, Vol. 2, No. 4, ISSN: 2296-1739, 56-66.
  2. Durairaj M. et al. 2013. "Data Mining Applications in Healthcare Sector: A Study", International Journal of Scientific and Technology Research, Vol. 2, ISSN 2277-8616.
  3. Hussan D. 2012. "Data Mining based Prediction of Medical data using K-means algorithm", Basrah Journal of Science(A), Vol. 30(1), 46-56.
  4. Jain N. et al. 2013. "Data Mining Techniques: A Survey Paper", International Journal of Research in Engineering and Technology, Volume: 02, Issue: 11, eISSN: 2319-1163 | pISSN: 2321-7308.
  5. Kharya S. 2012. "Using Data Mining Techniques for Diagnosis and Prognosis of Cancer Disease", International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol. 2, No. 2.
  6. Mittal P. et al. 2013. "Study and Analysis of Predictive Data Mining Approaches for Clinical Dataset", International Journal of Computer Applications, Volume 63, No. 3.
  7. Naib M. et al. 2014. "Predicting Primary Tumors using Multiclass Classifier Approach of Data Mining", International Journal of Computer Applications (0975 – 8887), Volume 96, No. 8.
  8. Qarzaie S. et al. "Using the Data Mining Techniques for Breast Cancer Early Prediction".
  9. Rani K. 2011. "Analysis of Heart Dksiseases Dataset Using Neural Network Approach", International Journal of Data Mining and Knowledge Management Process (IJDKP), Vol. 1, No. 5.
  10. Saurkar A. et al. 2014. "A Review Paper on various Data Mining Techniques", International Journal of Advance Research in Computer Science and Software Engineering, Volume 4, Issue 4, ISSN: 2277 128X, pp. 98-101.
  11. Sharma A. et al. 2012. "Predicting the Number of Blood Donors through their Age and Blood Group by using Data Mining Tool", International Journal of Communications and Computer Technologies, Volume 01, No. 6, ISSN Number: 2278-9723.
  12. Sharma A. et al. 2014. "Applications of Data Mining - A Survey Paper", International Journal of Computer Science and Information Technologies, Vol. 5(2), ISSN: 0975-9646, 2023 - 2025.
  13. Soni J. et al. 2011. "Predictive Data Mining Diagnosis: An Overview of Heart Disease Prediction", International Journal of Computer Applications (0975-8887), Vol. 17, No. 8.
  14. Upadhyay N. et al. 2014. "A Survey on the Classification Techniques in Educational Data Mining", International Journal of Computer Applications Technology and Research, Vol. 3, ISSN 2319-8656, pp. 725-728.
  15. Gennaro Costagliola et. al 2009. "Monitoring Online Tests through Data Visualization", IEEE Transactions on Knowledge & Data Engineering, Issue No. 06 – June, vol. 21, pp: 773-784.
Index Terms

Computer Science
Information Sciences

Keywords

Classification Decision Tree K means Clustering Naive Bayes WEKA