Fuzzy logic systems in cardiac dyssynchrony diagnostics
DOI:
https://doi.org/10.15587/2313-8416.2015.43286Keywords:
myocardial dyssynchrony, fuzzy logic, artificial neural network, automated system, functional diagnosticsAbstract
Aim – the development of a structural model of myocardial dyssynchrony, the construction of an artificial neural network of fuzzy inference based on this model for the diagnosis of myocardial dyssynchrony and determining the adequacy of the neural network into operation the automated system of diagnostics of myocardial dyssynchrony.
Methods of research – simulation modeling of diagnostic system based on real data of 40 patients. The fuzzy neural network is formed as a fuzzy (linguistic) value of estimation of dyssynchrony and dyssynchrony components and defuzzificated (numeric) values of these estimations. Diagnostic hypothesis, generated by automated system diagnostics, consistent with the results of an independent analysis of patients by twelve diagnosticians (so-called method of "Committee of Experts")
Results – evidence of the effectiveness of using fuzzy artificial neural network to diagnose myocardial dyssynchrony and the adequacy of the developed model of dyssynchrony.
Conclusion – the automated system of myocardial dyssynchrony diagnostics based on fuzzy neural network is a useful tool for diagnostician
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Copyright (c) 2015 Татьяна Анатольевна Руденко, Михаил Антонович Власенко
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