Application of fuzzy logic and genetic algorithm in heart disease risk level prediction
作者： Purushottam Sharma , Kanak Saxena
DOI: 10.1007/S13198-017-0578-8
关键词: Artificial intelligence 、 Identification (information) 、 Engineering 、 Fuzzy logic 、 Fuzzy set 、 Machine learning 、 Clinical decision support system 、 Genetic algorithm 、 Perspective (graphical) 、 Point (typography) 、 Heart disease risk
摘要: As individuals have intrigues in their wellbeing now a days, advancement of therapeutic area application has been standout amongst the most dynamic exploration territories. One case restorative is identification framework for coronary illness taking into account. A weighted fuzzy standard based clinical decision support system displayed conclusion illness, consequently acquiring learning from information. The proposed heart disease risk level prediction using and genetic forecast patients comprises two stages: (1) mechanized methodology era rules (2) building up principle algorithm. At this point, developed as per standards picked better qualities cases. In study, that can capably locate fundamentals to anticipate perspective given parameter about wellbeing. commitment study help non-specialized doctors settle on right choice level. framework’s execution assessed compared far precision concerned outcomes demonstrates incredible potential foreseeing more precisely.
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