Survey on Data Mining Algorithms in Disease Prediction

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2016 by IJCTT Journal
Volume-38 Number-3
Year of Publication : 2016
Authors : V.Kirubha, S.Manju Priya
DOI :  10.14445/22312803/IJCTT-V38P122

MLA

V.Kirubha, S.Manju Priya "Survey on Data Mining Algorithms in Disease Prediction". International Journal of Computer Trends and Technology (IJCTT) V38(3):124-128, August 2016. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Data mining is the process of extracting hidden interesting patterns from massive database. Medical domain contains heterogeneous data in the form of text, numbers and images that can be mined properly to provide variety of useful information for the physicians. The patterns obtained from the medical data can be useful for the physicians to detect diseases, predict the survivability of the patients after disease, severity of diseases etc. The main aim of this paper is to analyse the application of data mining in medical domain and some of the techniques used in disease prediction.

References
[1] Parvathi I, Siddharth Rautaray, ?Survey on Data Mining Techniques for the Diagnosis of Diseases in Medical Domain, International Journal of Computer Science and Information Technologies, Vol. 5 (1), 838-846, ISSN: 0975- 9646, 2014.
[2] Dhanya P Varghese, Tintu P B, ?A Survey on Health Data using Data Mining Techniques, International Research Journal of Engineering and Technology (IRJET), Volume: 02 Issue: 07, e-ISSN: 2395-0056, p-ISSN: 2395-0072, Oct- 2015.
[3] Vahid Rafe, Roghayeh Hashemi Farhoud, ?A Survey on Data Mining Approaches in Medicine, International Research Journal of Applied and Basic Sciences, Vol 4 (1), ISSN 2251-838X, 2013.
[4] www.medicalnewstoday.com/articles/237191.php
[5] www.heart.org/idc/groups/ahamahpublic/@ wcm/@sop/@smd/documents/downloadable/ucm- 480086.pdf
[6] T. Revathi, S. Jeevitha, ?Comparative Study on Heart Disease Prediction System Using Data Mining Techniques, Volume 4 Issue 7, ISSN (Online): 2319-7064, July 2015.
[7] Devendra Ratnaparkhi, Tushar Mahajan, Vishal Jadhav, ?Heart Disease Prediction System Using Data Mining Technique, International Research Journal of Engineering and Technology (IRJET), Volume: 02 Issue: 08, e-ISSN: 2395 -0056, p-ISSN: 2395-0072, Nov-2015.
[8] K.Manimekalai, ?Prediction of Heart Diseases using Data Mining Techniques, International Journal of Innovative Research in Computer andCommunication Engineering, Vol. 4, Issue 2, ISSN(Online):2320-9801, ISSN (Print):2320- 9798, February 2016.
[9] Jyoti Rohilla, Preeti Gulia, ?Analysis of Data Mining Techniques for Diagnosing Heart Disease”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 7, ISSN: 2277 128X, July 2015.
[10] www.niddk.nih.gov/health-information/healthcommunication- programs/nkdep/learn/causes-kidneydisease/ pages/disease-basics.asp
[11] www.kidney.org/kidneydisease/global-facts-about-kidneydisease/
[12] Dr. S. Vijayarani, Mr.S.Dhayanand, “Kidney Disease Prediction using SVM and ANN algorithms”, International Journal of Computing and Business Research (IJCBR), Volume 6, Issue 2, ISSN (Online):2229-6166, March 2015.
[13] Lambodar Jena, Narendra Ku. Kamila, “Distributed Data Mining Classification Algorithms for Prediction of Chronic- Kidney-Disease”, International Journal of Emerging Research in Management & Technology, Volume-4, Issue-11, and ISSN: 2278-9359, November 2015.
[14] Basma Boukenze, Hajar Mousannif and Abdelkrim Haqiq, “Performance of Data Mining Techniques to Predict in Healthcare Case Study: Chronic Kidney Failure Disease”, International Journal of Database Management Systems (IJDMS), Vol.8, No.3, June 2016.
[15] Pushpa M. Patil, “Review on Prediction of Chronic Kidney Disease using Data Mining Techniques”, International Journal of Computer Science and Mobile Computing, Vol. 5, ISSN 2320–088X, Issue. 5, May 2016.
[16] www.medicinenet.com
[17] www.britishlivertrust.org.uk/about-us/media-centre/factsabout- liver-disease/
[18] www.healthcommunities.com/liver-disease/causes.html
[19] D.Sindhuja, R. Jemina Priyadarsini, “A Survey on Classification Techniques in Data Mining for Analyzing Liver Disease Disorder”, International Journal of Computer Science and Mobile Computing, Vol.5, Issue.5, ISSN 2320– 088X, May 2016.
[20] A.S.Aneeshkumar, Dr. C.Jothi Venkateswaran, “A novel approach for Liver disorder Classification using Data Mining Techniques”, Engineering and Scientific International Journal (ESIJ), Volume 2, Issue 1, ISSN 2394- 7179 (Print), ISSN 2394-7187 (Online), January - March 2015.
[21] V.Shankar sowmien, V.Sugumaran, C.P.Karthikeyan, T.R.Vijayaram, “Diagnosis of Hepatitis using Decision tree algorithm”, International Journal of Engineering and Technology (IJET), Vol 8 No 3, e-ISSN : 0975-4024, p-ISSN : 2319-8613, Jun-Jul 2016.
[22] Dr. S. Vijayarani, Mr.S.Dhayanand, “Liver Disease Prediction using SVM and Naïve Bayes Algorithms, International Journal of Science, Engineering and Technology Research (IJSETR) Volume 4, Issue 4, ISSN: 2278 – 7798, April 2015.
[23] www.who.int/medicentre/factsheets
[24] Pragati Agrawal, Amit kumar Dewangan, “A Brief Survey on the Techniques used for the Diagnosis of Diabetes-Mellitus”, International Research Journal of Engineering and Technology (IRJET), Volume: 02 Issue: 03, e-ISSN: 2395 - 0056, p-ISSN: 2395-0072, June 2015.
[25] Ms. Nilam chandgude, Prof. Suvarna pawar, “A survey on diagnosis of diabetes using various classification algorithm”, International Journal on Recent and Innovation Trends in Computing and Communication, Volume: 3 Issue: 12, ISSN: 2321-8169, 6706 – 6710, December 2015.
[26] Thirumal P. C, Nagarajan N, ?Utilization of Data Mining Techniques for Diagnosis of Diabetes Mellitus- A Case Study”, ARPN Journal of Engineering and Applied Sciences, VOL. 10, NO. 1, ISSN 1819-6608, January 2015.
[27] K. Rajalakshmi, Dr. S. S. Dhenakaran, “Analysis of Datamining Prediction Techniques in Healthcare Management System”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 4, ISSN: 2277 128X, April 2015.
[28] www.who.int/mediacenter/factsheets/fs297
[29] Vikas Chaurasia, Saurabh Pal, “Data Mining Techniques: To Predict and Resolve Breast Cancer Survivability”, Vol. 3, Issue. 1, ISSN 2320–088X, January 2014.
[30] V.Krishnaiah, Dr. G. Narsimha, Dr. N. Subhash Chandra, “Diagnosis of Lung Cancer Prediction System Using Data Mining Classification Techniques”, International Journal of Computer Science and Information Technologies, Vol.4 (1), ISSN: 0975-9646, 2013.
[31] Durairaj M, Deepika R, “Prediction of Acute Myeloid Leukemia Cancer Using Data Mining- A Survey, Volume I, Issue 2, ISSN: 2394 – 6598, February 2015.
[32] Jothi Prabha A, A.Govardhan, “Application of Classification Techniques on Various Attributes of Breast Cancer”, Vol. 4, Issue 6, and ISSN (Online): 2320-9801, ISSN (Print): 2320- 9798, June 2016.

Keywords
Datamining, medical data, disease prediction.