Detection of cardiovascular disease risk’s level for adults using naive bayes classifier

Healthcare Informatics Research

Volumn 22, Issue 3, 2016, Pages 196-205

  Miranda, Eka ^a   Irwansyah, Edy ^a   Amelga, Alowisius Y ^a   Maribondang, Marco M ^a   Salim, Mulyadi ^a  

^a BINA NUSANTARA UNIVERSITY   (Indonesia)

Author keywords

Bayes Theorem; Cardiovascular Diagnostic Techniques; Cardiovascular Diseases; Classification; Data Mining

Indexed keywords

EID: 84981161278     PISSN: 20933681     EISSN: 2093369X     Source Type: Journal    
DOI: 10.4258/hir.2016.22.3.196     Document Type: Article

References (30)

1. Shouman M, Turner T, Stocker R. Using data mining techniques in heart disease diagnosis and treatment. Proceedings of Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC); 2012 Mar 6-9; Alexandria, Egypt. p. 173-7.
2. Ishtake SH, Sanap SA. Intelligent heart disease prediction system using data mining techniques. Int J Healthc Biomed Res 2013;1(3):94-101.
3. Ministry of Health Republic of Indonesia. Healthy environment, healthy heart [Internet]. Jakarta: Ministry of Health Republic of Indonesia; 2014 [cited at 2016 Jan 17]. Available from: http://www.depkes.go.id/article/view/201410080002/lingkungan-sehat-jantung-sehat.html.
4. World Health Organization, Department of Health Statistics and Information Systems. Global Health Estimates: key figures and tables [Internet]. Geneva: World Health Organization; 2016 [cited at 2016 Jan 17]. Available from: http://www.who.int/healthinfo/global_burden_disease/en.
5. Ministry of Health Republic of Indonesia. Heart health situation [Internet]. Jakarta: Ministry of Health Republic of Indonesia; 2014 [cited at 2016 Jan 17]. Available from: http://www.depkes.go.id/folder/view/01/struc-ture-publikasi-pusdatin-info-datin.html.
6. Marcovina SM, Crea F, Davignon J, Kaski JC, Koenig W, Landmesser U, et al. Biochemical and bioimaging markers for risk assessment and diagnosis in major cardiovascular diseases: a road to integration of complementary diagnostic tools. J Intern Med 2007;261(3):214-34.
7. Miao C, Bao M, Xing A, Chen S, Wu Y, Cai J, et al. Cardiovascular health score and the risk of cardiovascular diseases. PLoS One 2015;10(7):e0131537.
8. National Institutes of Health, National Heart, Lung, and Blood Institute. How is heart disease diagnosed? [Internet]. Washington (DC): National Institutes of Health; 2014 [cited at 2016 Jan 17]. Available from: http://www. nhlbi.nih.gov/health/health-topics/topics/hdw/diagnosis.
9. Sun X, Jia Z. A brief review of biomarkers for preventing and treating cardiovascular diseases. J Cardiovasc Dis Res 2012;3(4):251-4.
10. El-Sappagh SH, El-Masri S, Riad AM, Elmogy M. Data mining and knowledge discovery: applications, techniques, challenges and process models in healthcare. Int J Eng Res Appl 2013;3(3):900-6.
11. Cortes PL, Cortes EG. Hospital information systems: a study of electronic patient records. J Inf Syst Technol Manag 2011;8(1):131-54.
12. Qiu Y, Zhen S, Zhou M, Li L. Continuously improve the medical care quality and hospital management level through medical information system construction. J Transl Med 2012;10(Suppl 2):A56.
13. Butler J, Kalogeropoulos A. Hospital strategies to reduce heart failure readmissions: where is the evidence? J Am Coll Cardiol 2012;60(7):615-7.
14. Anbarasi M, Anupriya E, Iyengar NC. Enhanced prediction of heart disease with feature subset selection using genetic algorithm. Int J Eng Sci Technol 2010;2(10):5370-6.
15. Nishimura RA, Otto CM, Bonow RO, Carabello BA, Erwin JP 3rd, Guyton RA, et al. 2014 AHA/ACC guideline for the management of patients with valvular heart disease: executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol 2014; 63(22):2438-88.
16. Krum H, Driscoll A. Management of heart failure. Med J Aust 2013;199(5):334-9.
17. Holzinger A, Dehmer M, Jurisica I. Knowledge discovery and interactive data mining in bioinformatics: state-of-the-art, future challenges and research directions. BMC Bioinformatics 2014;15 Suppl 6:I1.
18. Roque FS, Jensen PB, Schmock H, Dalgaard M, Andre-atta M, Hansen T, et al. Using electronic patient records to discover disease correlations and stratify patient cohorts. PLoS Comput Biol 2011;7(8):e1002141.
19. Palaniappan S, Awang R. Intelligent heart disease prediction system using data mining techniques. Int J Comput Sci Netw Secur 2008;8(8):343-50.
20. Soni J, Ansari U, Sharma D, Soni S. Predictive data mining for medical diagnosis: an overview of heart disease prediction. Int J Comput Appl 2011;17(8):43-8.
21. Sakthimurugan T, Poonkuzhali S. An effective retrieval of medical records using data mining techniques. Int J Pharm Sci Health Care 2012;2(2):72-8.
22. Chaurasia V, Pal S. Early prediction of heart diseases using data mining techniques. Caribb J Sci Technol 2013; 1:208-17.
23. Das R, Turkoglu I, Sengur A. Effective diagnosis of heart disease through neural networks ensembles. Expert Syst Appl 2009;36(4):7675-80.
24. Sudhakar K, Manimekalai M. Propose a enhanced framework for prediction of heart disease. Int J Eng Res Appl 2015;5(4):1-6.
25. Rajkumar A, Reena GS. Diagnosis of heart disease using datamining algorithm. Glob J Comput Sci Technol 2010;10(10):38-43.
26. Jabbar MA, Deekshatulu BL, Chandra P. Classification of heart disease using k-nearest neighbor and genetic algorithm. Procedia Technol 2013;10:85-94.
27. Archana S, Elangovan K. Survey of classification techniques in data mining. Int J Comput Sci Mob Appl 2014; 2(2):65-71.
28. Han J, Kamber M. Data mining: concepts and techniques. 3rd ed. Amsterdam: Morgan Kaufmann; 2012.
29. Subbalakshmi G, Ramesh K, Rao MC. Decision support in heart disease prediction system using naive Bayes. Indian J Comput Sci Eng 2011;2(2):170-6.
30. Wiharto W, Kusnanto H, Herianto H. Intelligence system for diagnosis level of coronary heart disease with K-Star algorithm. Healthc Inform Res 2016;22(1):30-8.