An expert system based on linear discriminant analysis and adaptive neuro-fuzzy inference system to diagnosis heart valve diseases

Expert Systems with Applications

Volumn 35, Issue 1-2, 2008, Pages 214-222

  Sengur, Abdulkadir ^a  

^a FIRAT UNIVERSITY   (Turkey)

Author keywords

Adaptive neuro fuzzy inference system; Doppler heart sounds; Feature extraction; Feature reduction; Heart valves; Wavelet decomposition

Indexed keywords

ADMINISTRATIVE DATA PROCESSING; ARTIFICIAL INTELLIGENCE; BIONICS; CLASSIFICATION (OF INFORMATION); COMPUTER NETWORKS; DECISION SUPPORT SYSTEMS; DISCRIMINANT ANALYSIS; EIGENVALUES AND EIGENFUNCTIONS; EXPERT SYSTEMS; EXTRACTION; FEATURE EXTRACTION; FILTRATION; FOURIER TRANSFORMS; FUZZY INFERENCE; FUZZY SYSTEMS; IMAGE RETRIEVAL; MANAGEMENT INFORMATION SYSTEMS; MATHEMATICAL TRANSFORMATIONS; SENSITIVITY ANALYSIS; SENSORS; SIGNAL DETECTION; SOLVENT EXTRACTION; STAGES; VALVES (MECHANICAL); WAVELET TRANSFORMS;

(ALGORITHMIC) COMPLEXITY; ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS); AND DETECTION; ANFIS CLASSIFIER; APPLIED (CO); BIOMEDICAL ANALYSIS; COMPARATIVE STUDIES; DATA SETS; DE-NOISING; DETECTION SYSTEMS; DOPPLER; ELSEVIER (CO); FEATURE REDUCTION; HEART SOUND (HS); HEART VALVES; LINEAR DISCRIMINANT ANALYSIS (CLDA); MEDICAL EXPERTS; PRE-PROCESSING; SENSITIVITY AND SPECIFICITY; SHORT-TIME FOURIER TRANSFORM (STFT); WAVELET ENTROPY;

FUZZY LOGIC;

EID: 44949179538     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2007.06.012     Document Type: Article

References (25)

1. Akay M., Akay Y.M., and Welkowitz W. Neural networks for the diagnosis of coronary artery disease. International Joint Conference on Neural Networks, IJCNN 2 (1992) 419-424
2. Bakhtazad A., Palazoglu A., and Romagnoli J.A. Process data de-noising using wavelet transform. Intelligent Data Analysis 3 October (1999) 267-285
3. Chan B.C.B., Chan F.H.Y., Lam F.K., Lui P.W., and Poon P.W.F. Fast detection of venous air embolism is doppler heart sound using the wavelet transform. IEEE Transactions on Biomedical Engineering 44 4 (1997) 237-245
4. Coifman R.R., and Wickerhauser M.V. Entropy-based Algorithms for best basis selection. IEEE Transactions on Information Theory 38 2 (1992) 713-718
5. Çomak E., Arslan A., and Türkoǧlu I. A decision support system based on support vector machines for diagnosis of the heart valve diseases. Computers in Biology and Medicine 37 (2007) 21-27
6. Devasahayam S.R. Signals and Systems in Biomedical Engineering (2000), Kluwer Academic Publishers
7. Guler I., Kiymik M.K., Kara S., and Yuksel M.E. Application of autoregressive analysis to 20 MHz pulsed Doppler data in real time. International Journal Biomedical Computing 31 3-4 (1992) 247-256
8. Güler I., and Übeyli E.D. Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients. Journal of Neuroscience Methods 148 2 (2005) 113-121
9. http://hcd2.bupa.co.uk/fact_sheets/html/heart_valve_disease.html. accessed 01.12.2006.
10. http://www.healthsystem.virginia.edu/uvahealth/adult_cardiac/disvalve.cfm. accessed 01.12.2006.
11. Jang J.-S.R. ANFIS: Adaptive-network-based fuzzy inference system. IEEE Transactions on Systems Management Cybernetics 23 3 (1993) 665-685
12. Jing, F., Xuemin, W., Mingshi, W., & Wie, L. (1997). Noninvasive acoustical analysis system of coronary heart disease. Biomedical Engineering Conference, Proceedings of the 1997 Sixteenth Southern, pp. 239-241.
13. Karabetsos E., Papaodysseus C., and Koutsouris D. Design and development of a new ultrasonic doppler technique for estimation of the aggregation of red blood cells. Elsevier Meas 24 (1998) 207-215
14. Keeton, P. I. J., Schlindwein, F. S. (1997). Application of wavelets in Doppler ultrasound. MCB University Press, Vol. 17, Number 1, pp. 38-45.
15. Kim, H. C., Kim, D. J., & Bang, S. Y., (2002). "Face Recognition Using LDA Mixture Model." Proceedings 16th International Conference on Pattern Recognition, Vol. 2, pp. 925-928.
16. Lee, J., Park, K. L., Song, M. H., & Lee, K. J., (2005). Arrhythmia Classification with Reduced Features by Linear Discriminant Analysis. Engineering in Medicine and Biology 27th Annual Conference Shanghai, China, September 1-4, 2005.
17. Martinez A.M., and Kak A.C. PCA versus LDA. IEEE Transactions on Pattern Analysis and Machine Intelligence 23 2 (2001) 228-233
18. Nanda N.C. Doppler Echocardiography. 2nd ed. (1993), Lea and Febiger, London
19. Plett, M. I. (2000). Ultrasonic arterial vibrometry with wavelet based detection and estimation. University of Washington, Ph.D. Thesis, pp. 17-18.
20. Quiroga R.Q. Quantitative analysis of EEG signals: Time-frequency methods and chaos theory (1998), Intitute of Physiology - Medical University Lübeck
21. Quiroga, R. Q., Roso, O. A., & Basar, E. (1999). Wavelet entropy: A measure of order in evoked potentials. Elsevier Science, Evoked Potentials and Magnetic Fields, September, 49, pp. 298-302.
22. Saini V.D., Nanda N.C., and Maulik D. Basic Principles of Ultrasound and Doppler Effect. Doppler Echocardiography (1993), Lea and Febiger, Philadelphia, London
23. Turkoglu I., Arslan A., and Ilkay E. An expert system for diagnosis of the heart valve diseases. Expert Systems with Applications 23 (2002) 229-236
24. Uguz, H., Arslan, A., & Türkoǧlu, I. (2007). A biomedical system based on hidden Markov model for diagnosis of the heart valve diseases, Pattern Recognition Letters. Available online 11 October, 2006.
25. 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 and Biology 23 5 (1997) 683-690