Recognition of Coronary Heart Disease Patients by RBF Neural Network Basing on Contents of Microelements in Human Blood | IEEE Conference Publication | IEEE Xplore

Recognition of Coronary Heart Disease Patients by RBF Neural Network Basing on Contents of Microelements in Human Blood


Abstract:

Radial-basis-function (RBF) artificial neural network was developed to recognize the coronary heart disease patients basing on the contents of microelements in human bloo...Show More

Abstract:

Radial-basis-function (RBF) artificial neural network was developed to recognize the coronary heart disease patients basing on the contents of microelements in human blood. Leave-one out method was used to train the model. After training, the RBF model was used to recognize the coronary heart disease patients. Results showed that the RBF model recognized the three samples correctly, and the accuracy of RBF model was higher than the BP model. It showed that the RBF model could recognize the patients more accurately and it has important theoretical meaning and application value.
Date of Conference: 12-14 December 2009
Date Added to IEEE Xplore: 31 December 2009
Print ISBN:978-0-7695-3865-5
Conference Location: Changsha, China

1 Introduction

The coronary heart disease is a kind of common and frequent bouts of disease which badly endanger the health and lives of human being. Moreover, recently, its incidence has increased and the ages of the patients have become younger and younger [1], therefore, as early as possible recognition of the coronary heart disease patients has significant meaning.

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References

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