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Study and Analysis of Predictive Data Mining Approaches for Clinical Dataset

by Pooja Mittal, Nasib Singh Gill
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 63 - Number 3
Year of Publication: 2013
Authors: Pooja Mittal, Nasib Singh Gill
10.5120/10449-5151

Pooja Mittal, Nasib Singh Gill . Study and Analysis of Predictive Data Mining Approaches for Clinical Dataset. International Journal of Computer Applications. 63, 3 ( February 2013), 35-39. DOI=10.5120/10449-5151

@article{ 10.5120/10449-5151,
author = { Pooja Mittal, Nasib Singh Gill },
title = { Study and Analysis of Predictive Data Mining Approaches for Clinical Dataset },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 63 },
number = { 3 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 35-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume63/number3/10449-5151/ },
doi = { 10.5120/10449-5151 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:13:13.609910+05:30
%A Pooja Mittal
%A Nasib Singh Gill
%T Study and Analysis of Predictive Data Mining Approaches for Clinical Dataset
%J International Journal of Computer Applications
%@ 0975-8887
%V 63
%N 3
%P 35-39
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data Mining is an assortment of effective tool set to perform the statistical analysis on an immense dataset and to retrieve the valuable information from the dataset. In this work we have carried out an analytical survey on predictive data mining approaches on clinical dataset. The clinical dataset processing is one of the effective and most sensitive area which is studied under an expert environment. The present paper discusses KDD, data mining with reference to clinical expert system analysis, different applications and the approaches that can be used for the predictive data mining in same area. The scope of this paper is confined to the prediction of a person disease, based on symptoms dataset. The strength of data mining approaches in diverse clinical applications is also analyzed.

References
  1. Debahuti Mishra, "Predictive Data Mining: Promising Future and Applications", Int. J. of Computer and Communication Technology, Vol. 2, No. 1, 2010
  2. E. Barati, M. Saraee, "A Survey on Utilization of Data Mining Approaches for Dermatological (Skin) Diseases Prediction", Cyber Journals: Multidisciplinary Journals in Science and Technology, Journal of Selected Areas in Health Informatics (JSHI): March Edition, 2011
  3. Krzysztof J. Cio, "Uniqueness of medical data mining", Artificial Intelligence in Medicine 26 (2002) 1–24
  4. Yavar Naddaf, "Data Mining in Health Informatics"
  5. S. P. Deshpande, "Data Mining system and applications: A Review",InternationalJournal of Distributed and Parallel systems (IJDPS) Vol. 1, No. 1, September 2010
  6. Jayanthi Ranjan, "Data mining in pharma sector:bene?ts", International Journal of Health Care Quality Assurance Vol. 22 No. 1, 2009 pp. 82-92
  7. Maragatham G, "a recent review on association rule mining", Maragatham G et al. / Indian Journal of Computer Science and Engineering (IJCSE), ISSN : 0976-5166 Vol. 2 No. 6 Dec 2011-Jan 2012
  8. Shital Shah, Andrew Kusiak, "Cancer gene searchwith data-mining and genetic algorithms", Computers in Biology and Medicine 37 (2007) 251 – 261
  9. Dave Smith, "Data Mining in the Clinical Research Environment", PhUSE 2007
  10. P. K. Anooj, "Clinical decision support system: Risk level prediction of heart disease using weighted fuzzy rules", Journal of King Saud University – Computer and Information Sciences (2012) 24, 27–40
  11. Yo-Ping Huang, "Using Fuzzy Data Mining to Diagnose Patients' Degrees of Melancholia", Mobile Multimedia/Image Processing, Security, and Applications 2011
  12. U Keerthika, R Sethukkarasi, "A rough set based fuzzy inference system for mining temporal medical databases", International Journal on Soft Computing (IJSC) Vol. 3, No. 3, August 2012
  13. T. T. Nguyen, "Predicting CardioVascular Risk Using Neural Net Techniques"
  14. R. Sethukkarasi, "An Intelligent System for Mining Temporal Rules in Clinical Databases using Fuzzy Neural Networks", European Journal of Scientific Research ISSN 1450-216X Vol. 70 No. 3 (2012), pp. 386-395
  15. K. Usha Rani, "Analysis of heart diseases dataset using neural network approach", International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol. 1, No. 5, September 2011
  16. Ying Li, Sharon Lipsky Gorman, "Section Classi?cation in Clinical Notes using Supervised Hidden Markov Model", IHI'10, November 11–12, 2010, Arlington, Virginia, USA
  17. Weiqiang Lin, "Temporal Data Mining Using Hidden Markov-Local Polynomial Model",
  18. Fahad Shahbaz Khan, "Data Mining in Oral Medicine Using Decision Trees", International Journal of Biological and Life Sciences 2008
  19. D. Shanthi, Dr. G. Sahoo," Decision Tree Classifiers to Determine the Patient's Post-Operative Recovery Decision", International Journal of Artificial Intelligence and Expert Systems (IJAE), Volume (1): Issue (4)
Index Terms

Computer Science
Information Sciences

Keywords

Clinical Predictive Expert System Application Mining Approaches