CFP last date
20 December 2024
Reseach Article

Fuzzy based Congestive Heart Failure Diagnosis and Analysis

by Sharat Chandra
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 105 - Number 6
Year of Publication: 2014
Authors: Sharat Chandra
10.5120/18379-9614

Sharat Chandra . Fuzzy based Congestive Heart Failure Diagnosis and Analysis. International Journal of Computer Applications. 105, 6 ( November 2014), 5-8. DOI=10.5120/18379-9614

@article{ 10.5120/18379-9614,
author = { Sharat Chandra },
title = { Fuzzy based Congestive Heart Failure Diagnosis and Analysis },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 105 },
number = { 6 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume105/number6/18379-9614/ },
doi = { 10.5120/18379-9614 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:36:58.827105+05:30
%A Sharat Chandra
%T Fuzzy based Congestive Heart Failure Diagnosis and Analysis
%J International Journal of Computer Applications
%@ 0975-8887
%V 105
%N 6
%P 5-8
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The main target of this research is to design a Fuzzy Based Expert System for the diagnosis and analysis of congestive heart failure (CHF). The designed system has seven inputs like breathing problem, cough, heart rate, swelling, weight gain, urination, lack energy. The output field provide the stage of CHF in the patient. There are four stages stage1, stage2, stage3 and stage4. It is an integer valued from 0 (means no presence) to 1 (which is distinguish presence). Various membership functions are used for different symptoms. The proposed fuzzy expert system uses Mamdani inference method. The input data is collected from a total of 10 people which consists of male and female with different working background. The results obtained from proposed expert system are compared with data in database and it is observed that results of proposed system are correct in 90% and also the expert system designed in Matlab software. This proposed expert system may be used as an alternative approach for existing methods to distinguish of congestive heart failure (CHF) presence. Heart failure is a common cardiovascular disease with high morbidity and mortality. Thus, an intelligent and accurate diagnostic system is needed in order to threat the CHF patients. The linguistic variables, diagnosis process and their values were modeled based upon expert's knowledge and from existing literature survey. It is expected that the proposed Fuzzy Expert System can provide a cheaper, faster and more approximate result compared with other traditional methods available today. Congestive heart failure (CHF) is almost common clinical disorder that results in pulmonary vascular congestion and reduced cardiac output. Patients with CHF are suffer with pulmonary complications, including obstructive sleep problem, edema (pulmonary), and pleural effusions.

References
  1. Nadar S, Prasad N, Taylor RS, Lip GY. Positive pressure ventilation in the management of acute and chronic cardiac failure: a systematic review and meta-analysis. Int J Cardiol 2005; 99(2):171–185.
  2. Khand A, Gemmel I, Clark AL, Cleland JG. Is the prognosis of heart failure improving? J Am Coll Cardiol 2000; 36(7):2284–2286.
  3. McMurray JJ, Pfeffer MA. Heart failure. Lancet 2005; 365(9474):1877–1889.
  4. Brausnwald E. Disorders of the heart: normal and abnormal myocardial function. In: Fauci AS, editor. Harrison's principles of internal medicine, 14th Ed. New York: McGraw-Hill; 1998: 1278–1286.
  5. Aurigemma GP, Gaasch WH. Clinical practice: diastolic heart failure. N Engl J Med 2004; 351(11):1097–1105.
  6. Kitzman DW. Exercise intolerance. Prog Cardiovasc Dis 2005; 47(6): 367–379.
  7. Mancini DM. Pulmonary factors limiting exercise capacity in patients with heart failure. Prog Cardiovasc Dis 1995; 37(6):347–370.
  8. Choudhury L, Gheorghiade M, Bonow RO. Coronary artery disease in patients with heart failure and preserved systolic function. Am J Cardiol 2002; 89(6):719–722.
  9. Jessup M, Brozena S. Heart failure. N Engl J Med 2003; 348(20): 2007–2018
  10. Kendall, K. E. and Kendall, J. E. 2002. System Analysis and Design, Fifth Edition, Prentice-Hall International: Princeton, NJ.
  11. Ludmila, I. K. and Steimann F. 2008. Fuzzy Medical Diagnosis. School of Mathematics, University of Wales: Banggor, UK.
  12. Mihaela, U. 2003. "Internet-Enabled Soft Computing Holarchies for e-Health Applications". In: New Directions in Enhancing the Power of the Internet. L. A. Zadeh and M. Nikravesh (editors). Springer Verlag: Berlin, Germany.
  13. Merouani, M. , Guignard, B. , Vincent, F. , Borron,S. W. , Karoubi, P. , Fosse, J. P. , Cohen, Y. , Clec'h, C. , Vicaut, E. , Marbeuf-Gueye, C. , Lapostolle, F. , and Adnet, F. 2009. "Can Fuzzy Logic Make Things More Clear?" Critical Care. 13:116.
  14. Odejobi, O. A. 1997. Introduction to ArtificialIntelligence. First Edition. Dove Power Technology: Ile-Ife, Nigeria.
  15. Ogah, O. S. 2006. "Hypertension in Nigeria". A Global Community Promoting Cardiovascular Health: Lagos, Nigeria.
Index Terms

Computer Science
Information Sciences

Keywords

Congestive heart failure CHF Fuzzy logic Expert system membership function . heart . diagnosis analysis