Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
An Analysis of the Fundamental Structure of Complex-Valued Neurons
Neural Processing Letters
Computers in Biology and Medicine
Spectral analysing of portal vein Doppler signals in the cirrhosis patients
Computers in Biology and Medicine
A New Method for Diagnosis of Cirrhosis Disease: Complex-valued Artificial Neural Network
Journal of Medical Systems
A fuzzy clustering neural network architecture for classification of ECG arrhythmias
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
TAINN'05 Proceedings of the 14th Turkish conference on Artificial Intelligence and Neural Networks
Hi-index | 12.05 |
In this study, fuzzy clustering complex-valued neural network (FCCVNN) was proposed to classify portal vein Doppler signals recorded from 54 patients with cirrhosis and 36 healthy subjects. This proposed neural network is a new model for biomedical pattern classification. The FCCVNN was composed of three phases: fuzzy clustering, calculation of FFT values and complex-valued neural network (CVNN). In first phase, fuzzy clustering was done to reduce the number of segments in training pattern. After that, FFT values of Doppler signals were calculated for pre-processing and then obtained values, which include real and imaginary components, were used as the inputs of the CVNN for classification of Doppler signals. Classification results of FCCVNN were evaluated by the different performance evaluation criterion in literature. It shows that Doppler signals were classified successfully with 100% correct classification rate using the proposed method. Moreover, the rates of sensitivity and specificity were calculated as 100% using FCCVNN method. These results were seen to be appropriate with the expected results that are derived from physician's direct diagnosis. This method would be assisted the physician to make the final decision.