Application of fuzzy logic and genetic algorithm in heart disease risk level prediction

Purushottam Sharma () and Kanak Saxena ()
Additional contact information
Purushottam Sharma: Rajiv Gandhi Proudyogiki Vishwavidyalaya
Kanak Saxena: S.A.T.I.

International Journal of System Assurance Engineering and Management, 2017, vol. 8, issue 2, No 46, 1109-1125

Abstract: Abstract As individuals have intrigues in their wellbeing now a days, advancement of therapeutic area application has been a standout amongst the most dynamic exploration territories. One case of the restorative area application is the identification framework for coronary illness taking into account. A weighted fuzzy standard based clinical decision support system is displayed for the conclusion of coronary illness, consequently acquiring learning from the clinical information. The proposed heart disease risk level prediction system using fuzzy and genetic for the risk forecast of heart patients comprises of two stages: (1) mechanized methodology for the era of weighted fuzzy rules and (2) building up a fuzzy principle based heart disease risk level prediction using genetic algorithm. At this point, the fuzzy framework is developed as per the weighted fuzzy standards and picked better qualities cases. In this study, a system that can capably locate the fundamentals to anticipate the risk level of patients in perspective of the given parameter about their wellbeing. The principle commitment of this study is to help a non-specialized doctors to settle on right choice about the coronary illness risk level. The framework’s execution is assessed and compared as far as rules precision concerned and the outcomes demonstrates that the framework has incredible potential in foreseeing the coronary illness risk level more precisely.

Keywords: Heart disease risk level prediction; Fuzzy set; Fuzzy logic; Genetic algorithms; UCI; Learning systems (search for similar items in EconPapers)
Date: 2017
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
http://link.springer.com/10.1007/s13198-017-0578-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-017-0578-8

Ordering information: This journal article can be ordered from
http://www.springer.com/engineering/journal/13198

DOI: 10.1007/s13198-017-0578-8

Access Statistics for this article

International Journal of System Assurance Engineering and Management is currently edited by P.K. Kapur, A.K. Verma and U. Kumar

More articles in International Journal of System Assurance Engineering and Management from Springer, The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().