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

Author

Listed:
  • Purushottam Sharma

    (Rajiv Gandhi Proudyogiki Vishwavidyalaya
    Amity University)

  • Kanak Saxena

    (S.A.T.I.)

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.

Suggested Citation

  • Purushottam Sharma & Kanak Saxena, 2017. "Application of fuzzy logic and genetic algorithm in heart disease risk level prediction," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(2), pages 1109-1125, November.
    • Handle: RePEc:spr:ijsaem:v:8:y:2017:i:2:d:10.1007_s13198-017-0578-8
    DOI: 10.1007/s13198-017-0578-8
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    Cited by:

    1. Do Ngoc Tuyen & Tran Manh Tuan & Le Hoang Son & Tran Thi Ngan & Nguyen Long Giang & Pham Huy Thong & Vu Van Hieu & Vassilis C. Gerogiannis & Dimitrios Tzimos & Andreas Kanavos, 2021. "A Novel Approach Combining Particle Swarm Optimization and Deep Learning for Flash Flood Detection from Satellite Images," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    2. Rasool Motahari & Yasser Saeidi Sough & Hamed Aboutorab & Morteza Saberi, 2021. "Joint optimization of maintenance and inventory policies for multi-unit systems," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(3), pages 587-607, June.
    3. Richa Sharma & Purushottam Sharma & Anshuman Singh & Veer Srivastava, 2023. "An approach to optimize performance of controller in networked control system," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(5), pages 1639-1646, October.
    4. Purushottam Sharma & Shaurya Kapoor & Richa Sharma, 2023. "Ransomware detection, prevention and protection in IoT devices using ML techniques based on dynamic analysis approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 287-296, February.
    5. Hadef Hefaidh & Djebabra Mébarek, 2020. "A conceptual framework for risk matrix capitalization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 755-764, June.

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