Computational intelligence technique for early diagnosis of heart disease

ICETECH 2015 - 2015 IEEE International Conference on Engineering and Technology

Volumn , Issue , 2015, Pages

  Jabbar, M A ^a   Deekshatulu, B L ^b   Chandra, Priti ^c  

^a Aurora Engineering College   (India)

^b INSTITUTE FOR DEVELOPMENT AND RESEARCH IN BANKING TECHNOLOGY   (India)

^c DRDO   (India)

Author keywords

classification; computational intelligence; data mining; heart disease; naive bayes

Indexed keywords

ARTIFICIAL INTELLIGENCE; CARDIOLOGY; CLASSIFIERS; DATA MINING; DIAGNOSIS; DISCRETE EVENT SIMULATION; DISEASES; GENETIC ALGORITHMS; HEART; OPTIMIZATION;

COMPUTATIONAL INTELLIGENCE TECHNIQUES; DISCRETIZATION METHOD; HEART DISEASE; HEART DISEASE DIAGNOSIS; NAIVE BAYES; NAIVE BAYES CLASSIFIERS; OPTIMIZATION PROBLEMS; PREDICTIVE ACCURACY;

CLASSIFICATION (OF INFORMATION);

EID: 84965014018     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICETECH.2015.7275001     Document Type: Conference Paper

References (25)

1. M.A Jabbar, B.L Deekshatulu, Priti Chandra," Heart disease classification using nearest neighbor classifier with feature subset selection", Annals Computer science series,Vol XI,Fasc 1,pp 47-54 (2013)
2. Smith J.S,"Screening for high risk cardio vascular disesase: A challenge for the guidelines, Archives of internal medicine", 170, 40-42(2010)
3. Zhang.H,"The optimality of naïve bayes", American association of artificial intelligence" (2004)
4. Kai Ming Ting," A study of ADA Boost with naïve Bayesian classifiers: Weakness and improvement", Computational intelligence, Vol 19, No 2, pp 186-200(2003)
5. Jasmine Novakovic et.al,"Toward optimal feature selection using ranking methods and classification algorithms", Yugoslav journal of operations research", 21,pp119-125(2011)
6. Saba Bashir et.al,"An ensemble based decision support framework for intelligent heart disease diagnosis', I society pp 259-264(2014)
7. Naïve bayes classifier," http://en.wikipedia.org/wiki/naivibayes
8. Qinbao Song et.al,"A fast clustering based feature selection algorithm for high dimensional data", IEEE transactions on knowledge and data engineering", Vol 25, No 1(2013)
9. Ping-Ning Tan et.al, "Introduction to data mining", Pearson Education (2006)
10. Hall M.A and Smith L.A, "Feature selection for machine learning: Comparing a correlated based filter approach to the wrapper: In Proc.of Twelfth IFAIRSC, pp 235-239(1999)
11. M.A Jabbar, B.L Deekshatulu, Priti Chandra, "Classification of heart disease using artificial neural network and feature subset selection",GJCST,Vol13,Issue 3,pp 4-14(2013)
12. M.A Jabbar, B.L Deekshatulu, Priti Chandra," Prediction of risk score for heart disease using associative classification and hybrid feature subset selection", In.Proc of 12th ISDA, IEEE,pp 628-634(2012)
13. Anne F.Maberi,"Chi Square Test", Statistics for the social sciences, Last accessed (16/1/2015)
14. T.K.V Iyengar et.al,"Probability and statistics", S.Chand publishers, pp 301-302(2008)
15. Holte,R.C,"Very simple classification rules perform well on most commonly used data sets", Machine learning,Vol 11,pp 63-91(1993)
16. Noureddin Sadawi,"The One-R Classifier, what it is and how it works", (27th August 2014)
17. Robnik-Sikonja et.al,"Theoretical and empire analysis of relief and relief-F", Machine learning, Vol 53, pp23-69(2003)
18. M.A Jabbar, B.L Deekshatulu, Priti Chandra," Knowledge discovery from mining association rules for heart disease prediction",Vol 41,No 2,pp 45-53,JATIT(2012)
19. WHO Report on non communicable diseases September (2011)
20. Aha.D and Kibler,"Instance based prediction of heart disease presence with the Cleveland data base", Technical report, ICS-TR-88-07
21. T.John peter et.al,"Study and development of novel feature subset selection framework for heart disease prediction", IJSRP, Vol 2, Issue 10, Oct 9 (2012)
22. Mai shouman et.al,"Integrating naïve bayes and K-Means clustering with different initial centroid selection methods in the diagnosis of heart disease patients", CS&IT-CSCP, pp 125-137(2012)
23. M.S Rupali R Patil, "Heart disease prediction system using naïve bayes and Jelmek-mercer Smoothing", IJARCCE, Vol 3, Issue 5, pp 6787-6792(2014)
24. Elma Zannatul Ferdousy et.al,"Combination of naïve bayes classifier and K-NN in the classification based predictive models", Computer and information science, Vol 6, No 3, pp 48-56(2013)
25. http://archieve.ics.uci.edu/ml/datasets