Title :
Recognition of Coronary Heart Disease Patients by RBF Neural Network Basing on Contents of Microelements in Human Blood
Author :
You, Wei ; Wang, Yang ; Wo, Baoan ; Lv, Shuiqing ; Zhan, Aili ; Sun, Wenjing
Author_Institution :
Dept. of Mech. & Electr. Eng., North China Inst. of Sci. & Technol., Beijing, China
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.
Keywords :
backpropagation; blood; cardiology; diseases; medical computing; radial basis function networks; BP model; RBF neural network; coronary heart disease patient recognition; human blood microelements; leave-one out method; Accuracy; Artificial neural networks; Blood; Cardiac disease; Cardiovascular diseases; Humans; Neural networks; Predictive models; Strontium; Zinc;
Conference_Titel :
Computational Intelligence and Design, 2009. ISCID '09. Second International Symposium on
Conference_Location :
Changsha
Print_ISBN :
978-0-7695-3865-5
DOI :
10.1109/ISCID.2009.248
