Analytical Study of Data Mining Predictive Techniques For Health Care
Keywords:
Data mining technique, Algorithm, Predictive Algorithm, Data mining for Health Care, Association Rule mining, Pattern, Binary patternAbstract
Data mining techniques or algorithm is the way which is used to perform the automated operation to take decision based on findings. Algorithm is a procedure or step-by-step logical solution for solving data mining problem, algorithm takes some inputs as a parameter and produce some result as a solution of problem. Another way we defined data mining technique as a data mining algorithm. We have studied various algorithms and techniques such as Classification, Clustering, Regression, Artificial Intelligence, Neural Networks, Association Rules, Decision Trees, Genetic Algorithm, Nearest Neighbor method etc. Here in this paper we have given an algorithm based on clustering objects which is useful to predict possibilities of diseases in particular cases. Algorithm gives the result which is depends on diseases table data for prediction. To analysis the algorithm we have taken graph architecture, which gives the pattern of relationships.
References
- Porkizhi M.,”A Study of Data Mining Techniques And Its Applications”, IJSART, ISSN [ONLINE]: 2395-1052, Volume 3 Issue 4, APRIL 2017
- K.Srinivas et al., "Applications of Data Mining Techniques in Healthcare and Prediction of Heart Attacks", International Journal on Computer Science and Engineering Vol. 02, No. 02, pp. 250-255, 2010
- Chowdary B V,Radhika Y.,"A Survey on Applications of Data Mining Techniques" International Journal of Applied Engineering Research ISSN 0973-4562, Volume 13, pp.5384-5392, Number 7, 2018.
- Tamilselvi1 R., Kalaiselvi S.,"An Overview of Data Mining Techniques and Applications", International Journal of Science and Research (IJSR), India Online ISSN: 2319‐7064,Volume 2 Issue 2, February 2013
- Jain Nikita, Srivastava Vishal,"DATA MINING TECHNIQUES: A SURVEY PAPER", IJRET: International Journal of Research in Engineering and Technology, Volume: 02 Issue: 11, Nov-2013.
Downloads
Published
Issue
Section
License
Copyright (c) IJSRCSEIT

This work is licensed under a Creative Commons Attribution 4.0 International License.