The data mining techniques is a major significant position in the field of healthcare and medical industry to analyze the medical data and finding the patterns from those data. The primary goal of the research analysis work is to predict the patient diseases from the medical data sets. Medical practitioners is getting difficult to predict the disease, actually it is one of the complex task which require their experience and knowledge. The main objective of data mining techniques to predict the possible disease from patient dataset and based on patient serious condition priority wise to reduce the congestion in the network. In this paper proposed the genetic approach is efficient for associative classification algorithm to predict the disease. The motivation is by using genetic algorithm in the discovery of high level prediction rules which can be highly comprehensible having high predictive accuracy and high interestingness values.

Data Mining, Association Rule, Keyword Based Clustering, Genetic algorithm, Classification

[1] S. Vijayarani* and S. Sudha “An Efficient Clustering Algorithm for Predicting Diseases from Hemogram Blood Test Samples” Indian Journal of Science and Technology, Vol 8(17), August 2015.
[2] Aswathy Wilson, Gloria Wilson, Likhiya Joy K “Heart disease prediction using data mining techniques”
[3] G. Purusothaman* and P. Krishnakumari “A Survey of Data Mining Techniques on Risk Prediction: Heart Disease” Indian Journal of Science and Technology, Vol 8(12), DOI: 10.17485/ijst/2015/v8i12/58385, June 2015.
[4] Jyoti Soni Ujma Ansari Dipesh Sharma “Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease Prediction” international Journal of Computer Applications, Volume 17– No.8, March 2011
[5] Hnin Wint Khaing, “Data Mining based Fragmentation and Prediction of Medical Data”, International Conference on Computer Research and Development, ISBN: 978-1-61284-840-2,2011
[6]Himigiri. Danapana, M. Sumender Roy,‖ Effective Data Mining Association Rules for Heart Disease Prediction System‖ IJCST Vol. 2, Issue 4, Oct . - Dec. 2011.
[7]Fariba Shadabi and Dharmendra Sharma,‖ Artificial Intelligence and Data Mining Techniques in Medicine – Success Stories‖ International Conference on BioMedical Engineering and Informatics- 2008.
[8] J. Liu, Y.-T. HSU, and C.-L. Hung, “Development of Evolutionary Data Mining Algorithms and their Applications to Cardiac Disease Diagnosis,” in WCCI 2012 IEEE World Congress on Computational Intelligence, 2012, pp. 10–15.
[9] P. Chandra, M. . Jabbar, and B. . Deekshatulu, “Prediction of Risk Score for Heart Disease using Associative Classification and Hybrid Feature Subset Selection,” in 12th International Conference on Intelligent Systems Design and Applications (ISDA), 2012, pp. 628– 634.
[10] S. U. Amin, K. Agarwal, and R. Beg, “Genetic Neural Network Based Data Mining in Prediction of Heart Disease Using Risk Factors,” in Proceedings of 2013 IEEE Conference on Information and Communication Technologies (ICT 2013), 2013, no. Ict, pp. 1227– 1231.
[11]Zhao, Q., Rezaei, M., Chen, H., Franti, and P.: Keyword clustering for automatic categorization. Pattern Recognition (ICPR), 2012 21st International Conference on. IEEE, (2012).
[12]Michael Pucher, F. T. W.: Performance Evaluation of WordNet-based Semantic Relatedness Measures for Word Prediction in Conversational Speech. (2004).
[13] K. Sudhakar, “Study of Heart Disease Prediction using Data Mining,” vol. 4, no. 1, pp. 1157–1160, 2014.
[14] R. Chitra and V. Seenivasagam, “REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES,” Journal on Soft Computing (ICTACT), vol. 3, no. 4, pp. 605–609, 2013.
[15]. Shanta kumar, B.Patil,Y.S.Kumaraswamy, “Predictive data mining for medical diagnosis of heart disease prediction” IJCSE Vol .17, 2011
[16]. M. Anbarasi et. al. “Enhanced Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm”, International Journal of Engineering Science and Technology Vol. 2(10), 5370-5376 ,2010.
[17]. Hnin Wint Khaing, “Data Mining based Fragmentation and Prediction of Medical Data”, IEEE, 2011.
[18] MA.Jabbar, Priti Chandra, B.L.Deekshatulu..:Cluster based association rule mining for heart attack prediction,JATIT,vol 32,no2,(Oct 2011)
[19] Ping Ning tan, Steinbach, vipin Kumar. : Introduction to Data Mining, Pearson Education, (2006).
[20] Picek, S., Golub, M.: On the Efficiency of Crossover Operators in Genetic Algorithms with Binary Representation. In: Proceedings of the 11th WSEAS International Conference on Neural Networks (2010)
[21] P.S.Mishra “Optimization of the Radial Basis Function Neural Networks Using Genetic Algorithm for Stock Index Prediction”, International Journal of Computer Science and Engineering Vol. 6(6), 2347-2693, 2018.
[22] K. Sivaranjani, A. Nisha Jebaseeli “Survey on Disease Diagnostic using Data Mining Techniques”, International Journal of Computer Science and Engineering Vol. 6(2), 2347-2693 ,2018.