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Application of T-S fuzzy neural network to intelligent diagnosis of coronary heart disease

  • LIU Ming ,
  • NIE Lei ,
  • ZHOU Zhiqian
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  • 1. School of Mathematics and Statistics, Changchun University of Technology, Changchun 130012, China;
    2. Department of Electrical Engineering and Computer Science, University of Missouri, Columbia, Missouri 65211, USA

Received date: 2018-06-03

  Revised date: 2018-08-30

  Online published: 2018-09-18

Abstract

Coronary heart disease is one of the most common cardiovascular diseases. In recent years, the incidence and mortality of coronary heart disease in China have increased year by year. Accurate diagnosis and timely treatment are the main measures to effectively reduce the mortality of coronary heart disease. With the help of the fuzzy system theory and by adding a fuzzy layer and fuzzy rule calculation layer to the structure of a traditional BP neural network, a T-S fuzzy neural network model is established in this paper. Using this model, the 297 data sets of coronary heart disease collected from the Cleveland Clinic are analyzed for diagnostic prediction. The average accuracy of the fuzzy neural network model reaches 82.93%, which is higher than 75.56%, the average accuracy of the traditional BP neural network in intelligent diagnosis of coronary heart disease.

Cite this article

LIU Ming , NIE Lei , ZHOU Zhiqian . Application of T-S fuzzy neural network to intelligent diagnosis of coronary heart disease[J]. Science & Technology Review, 2018 , 36(17) : 91 -96 . DOI: 10.3981/j.issn.1000-7857.2018.17.011

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