Expert systems for time-varying biomedical signals using eigenvector methods

Expert Systems with Applications

Volumn 32, Issue 4, 2007, Pages 1045-1058

  Güler, Inan ^a   Übeyli, Elif Derya ^b  

^a GAZI UNIVERSITY   (Turkey)

^b TOBB UNIVERSITY OF ECONOMICS AND TECHNOLOGY   (Turkey)

Author keywords

Combined neural network (CNN); Eigenvector methods; Mixture of experts (ME); Modified mixture of experts (MME); Time varying biomedical signals

Indexed keywords

BIOMEDICAL ENGINEERING; CLASSIFICATION (OF INFORMATION); EIGENVALUES AND EIGENFUNCTIONS; FEATURE EXTRACTION; NEURAL NETWORKS; SIGNAL PROCESSING;

COMBINED NEURAL NETWORK (CNN); EIGENVECTOR METHODS; MIXTURE OF EXPERTS (ME); MODIFIED MIXTURE OF EXPERTS (MME); TIME-VARYING BIOMEDICAL SIGNALS;

EXPERT SYSTEMS;

EID: 33751437697     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2006.02.002     Document Type: Article

References (24)

1. Agarwal R., Gotman J., Flanagan D., and Rosenblatt B. Automatic EEG analysis during long-term monitoring in the ICU. Electroencephalography and Clinical Neurophysiology 107 1 (1998) 44-58
2. Akay M., Semmlow J.L., Welkowitz W., Bauer M.D., and Kostis J.B. Noninvasive detection of coronary stenoses before and after angioplasty using eigenvector methods. IEEE Transactions on Biomedical Engineering 37 11 (1990) 1095-1104
3. Andrzejak R.G., Lehnertz K., Mormann F., Rieke C., David P., and Elger C.E. Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: Dependence on recording region and brain state. Physical Review E 64 (2001) 061907
4. Chen K. A connectionist method for pattern classification with diverse features. Pattern Recognition Letters 19 7 (1998) 545-558
5. Chen K., Xu L., and Chi H. Improved learning algorithms for mixture of experts in multiclass classification. Neural Networks 12 9 (1999) 1229-1252
6. EEG time series. Available from http://www.meb.uni-bonn.de/epileptologie/science/physik/eegdata.html.
7. Güler İ., and Übeyli E.D. A mixture of experts network structure for modelling Doppler ultrasound blood flow signals. Computers in Biology and Medicine 35 7 (2005) 565-582
8. Güler İ., and Übeyli E.D. A modified mixture of experts network structure for ECG beats classification with diverse features. Engineering Applications of Artificial Intelligence 18 7 (2005) 845-856
9. Güler İ., and Übeyli E.D. ECG beat classifier designed by combined neural network model. Pattern Recognition 38 2 (2005) 199-208
10. Güler N.F., Übeyli E.D., and Güler İ. Recurrent neural networks employing Lyapunov exponents for EEG signals classification. Expert Systems with Applications 29 3 (2005) 506-514
11. Hong X., and Harris C.J. A mixture of experts network structure construction algorithm for modelling and control. Applied Intelligence 16 1 (2002) 59-69
12. Hu Y.H., Palreddy S., and Tompkins W.J. A patient-adaptable ECG beat classifier using a mixture of experts approach. IEEE Transactions on Biomedical Engineering 44 9 (1997) 891-900
13. Jacobs R.A., Jordan M.I., Nowlan S.J., and Hinton G.E. Adaptive mixtures of local experts. Neural Computation 3 1 (1991) 79-87
14. Jordan M.I., and Jacobs R.A. Hierarchical mixture of experts and the EM algorithm. Neural Computation 6 2 (1994) 181-214
15. Kordylewski H., Graupe D., and Liu K. A novel large-memory neural network as an aid in medical diagnosis applications. IEEE Transactions on Information Technology in Biomedicine 5 3 (2001) 202-209
16. Kwak N., and Choi C.-H. Input feature selection for classification problems. IEEE Transactions on Neural Networks 13 1 (2002) 143-159
17. Mangiameli P., and West D. An improved neural classification network for the two-group problem. Computers & Operations Research 26 5 (1999) 443-460
18. Nigam V.P., and Graupe D. A neural-network-based detection of epilepsy. Neurological Research 26 1 (2004) 55-60
19. Übeyli E.D., and Güler İ. Comparison of eigenvector methods with classical and model-based methods in analysis of internal carotid arterial Doppler signals. Computers in Biology and Medicine 33 6 (2003) 473-493
20. Übeyli E.D., and Güler İ. Feature extraction from Doppler ultrasound signals for automated diagnostic systems. Computers in Biology and Medicine 35 9 (2005) 735-764
21. Übeyli E.D., and Güler İ. Improving medical diagnostic accuracy of ultrasound Doppler signals by combining neural network models. Computers in Biology and Medicine 35 6 (2005) 533-554
22. Wolpert D.H. Stacked generalization. Neural Networks 5 (1992) 241-259
23. Wright I.A., Gough N.A.J., Rakebrandt F., Wahab M., and Woodcock J.P. Neural network analysis of Doppler ultrasound blood flow signals: A pilot study. Ultrasound in Medicine & Biology 23 5 (1997) 683-690
24. Wright I.A., and Gough N.A.J. Artificial neural network analysis of common femoral artery Doppler shift signals: Classification of proximal disease. Ultrasound in Medicine & Biology 24 5 (1999) 735-743