Diagnose System for Heart Risk with Fuzzy Controller
||International Journal of Computer & Organization Trends (IJCOT)||
|© 2016 by IJCOT Journal|
|Volume - 6 Issue - 1
|Year of Publication : 2016|
|Authors : Neeru Pathania, Ritika, Sanjeev|
|DOI : 10.14445/22492593/IJCOT-V31P301|
Neeru Pathania, Ritika, Sanjeev"Diagnose System for Heart Risk with Fuzzy Controller", International Journal of Computer & organization Trends (IJCOT), V6(1):65-68 Jan - Feb 2016, ISSN:2249-2593, www.ijcotjournal.org. Published by Seventh Sense Research Group.
Abstract The diagnose system for any disease are greatly required nowadays. The use of information technology in diagnosis and treatment of illnesses has highly increased. The recognition of heart disease from symptoms features or signs are a multi layered problem. The knowledge and experience of specialists and clinical data of patients assist the diagnosis procedure. The automated prediction about the heart disease of patient made treatment easy. The intelligent and effective heart attack prediction system using fuzzy inference system is designed in this paper. The main factors or symptoms of heart attack are discussed.
 Mendis, S., Puska, P., Norrving, B. (2011). Global Atlas on cardiovascular disease prevention and control. ISBN 978-92- 4-15637-3.
 Gale Nutrition Encyclopaedia (2011). Heart disease http://www.answers.com/topic/ischaemic heart disease (Accessed 25 February 2011).
 Merijohn G. K., Bader J. D., Frantsve-Hawley J.,(2008). Clinical decision support chair side tools for evidence-based dental practice. The Journal of Evidence-Based Dental Practice, 8 (3) 2008, pp.119–132.
 Garg N.K., Adhikari, McDonald H. (2005). Effects of computerized clinical decision support systems on practitioner performance and patient outcomes.Journal of the American Medical Association. Pub Med, 293 (10). pp. 1223–1238.
 Abbasi M.M., Kashiyarndi S. (2006). Clinical decision support systems: a discussion on different methodologies used in health care.
 Warren J., Beliakov G., Zwaag B. (2000). Fuzzy logic in clinical practice decision support system. In: Proceedings of the 33rd Hawaii International Conference on System Sciences, Maui, Hawaii. 4–7 January 2000.
 Anderson J., Clearing the way for physicians use of clinical information systems Communication of the ACM (1997), pp. 83–90.
 E. P. Ephzibah “Design of a Fuzzy-based Decision Support System for Coronary Heart Disease Diagnosis” Journal of Medical Systems October 2012, Volume 36, Issue 5, pp 3293-3306.
 Novruz Allahverdi & Serhat Torun & Ismail Saritas “Design of a Fuzzy Expert System for Determination of Coronary Heart Disease Risk” International Conference on Computer Systems and Technologies - CompSysTech?07.
 Manisha Barman, J Pal Choudhury” A Fuzzy Rule Base System for the Diagnosis of Heart Disease” International Journal of Computer Applications (0975 – 8887) Volume 57– No.7, November 2012.
 Ali Adele and Mehdi Neshat, “A fuzzy expert system for heart disease diagnosis”, International Multi-conference of engineers and computer scientists, 2010, Volume 1.
 M. Anbarasi, E. Anupriya, N. Ch. S. N. Iyengar “Enhance Prediction of Heart Disease with Feature Subset Selection using Genetic Algorithm” International Journal of Engineering and Technology Vol.2 (10), 2010, 5370-5376.
 E. P .Ephzibah and Dr. V Shrandhanjali “A Hybrid Genetic- Fuzzy Expert System for Effective Heart Disease Diagnosis”, International Journal of Latest Trends in Computing (EISSN: 2045- 5364) 165 Volume 2, Issue 1, March 2011.
 Vanisree K, Jyothi Singaraju, “Decision Support System for Congenital Heart Disease Diagnosis based on Signs and Symptoms using Neural Networks”, International Journal of Computer Applications (0975 – 8887),volume 19– No.6, April 2011. Pp: 6-12.
 A. Q. Ansari ,Neeraj Kumar Gupta “Automated Diagnosis of Coronary Heart Disease Using Neuro-Fuzzy Integrated System” IEEE Conference on Fuzzy Systems in 16-18 Jan 2011.
 Resul Das, Ibrahim Turkoglu, Abdulkadir Sengur, “Effective diagnosis of heart disease through neural networks ensembles", Expert systems with applications, vol. 36 number 4, may, 2009, pp: 7675–7680.
 K. Rajeswari, V. vaithiyanatham, P. Amirtharaj, ”Prediction of risk score for Heart Disease in india using Machine Intelligence”, International Conference on Information and network Technology 2011, IPCSIT Press, Singapore, vol no 4, pp: 18-22.
Fuzzy, Heart predictions, FIS.