Questionnaire- versus voice-based screening for laryngeal disorders

Expert Systems with Applications

Volumn 39, Issue 6, 2012, Pages 6254-6262

  Verikas, Antanas ^a,b   Bacauskiene, Marija ^a   Gelzinis, Adas ^a   Vaiciukynas, Evaldas ^a   Uloza, Virgilijus ^c  

^a KAUNAS UNIVERSITY OF TECHNOLOGY   (Lithuania)

^b HALMSTAD UNIVERSITY   (Sweden)

^c KAUNAS UNIVERSITY OF MEDICINE   (Lithuania)

Author keywords

Canonical correlation analysis; Curvilinear component analysis; Genetic search; Laryngeal disorder; Query data; SVM

Indexed keywords

CANONICAL CORRELATION ANALYSIS; CURVILINEAR COMPONENT ANALYSIS; GENETIC SEARCH; LARYNGEAL DISORDER; QUERY DATA; SVM;

HEALTH CARE; NONLINEAR ANALYSIS; SPEECH; SUPPORT VECTOR MACHINES; SURVEYS; VISUALIZATION;

DATA VISUALIZATION;

EID: 84856517657     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2011.12.037     Document Type: Article

References (28)

1. H. Altun, and G. Polat Boosting selection of speech related features to improve performance of multi-class svms in emotion detection Expert Systems with Applications 36 4 2009 8197 8203
2. M. Bacauskiene, A. Verikas, A. Gelzinis, and D. Valincius A feature selection technique for generation of classification committees and its application to categorization of laryngeal images Pattern Recognition 42 5 2009 645 654
3. H.U. Bauer, and K.R. Pawlezik Quantifying the neighbourhood preservation of self-organizing feature maps IEEE Transactions on Neural Networks 3 1992 570 579
4. C.M. Bishop, M. Svensen, and C.K.I. Williams GTM: The generative topographic mapping Neural Computation 10 1998 215 234 (Pubitemid 128463659)
5. I. Borg, and P.J.F. Groenen Modern multidimensional scaling: Theory and applications 1997 Springer-Verlag New York
6. P. Demartines, and J. Herault Curvilinear component analysis: A self-organizing neural network for nonlinear mapping of data sets IEEE Transactions on Neural Networks 8 1 1997 148 154 (Pubitemid 127767788)
7. A. Gelzinis, A. Verikas, and M. Bacauskiene Automated speech analysis applied to laryngeal disease categorization Computer Methods and Programs in Biomedicine 91 1 2008 36 47
8. J.I. Godino-Llorente, and P. Gomez-Vilda Automatic detection of voice impairments by means of short-term cepstral parameters and neural network based detectors IEEE Transactions on Biomedical Engineering 51 2 2004 380 384 (Pubitemid 38133618)
9. S. Hadjitodorov, and P. Mitev A computer system for acoustic analysis of pathological voices and laryngeal diseases screening Medical Engineering and Physics 24 2002 419 429 (Pubitemid 34808729)
10. J.F. Hair, R.E. Anderson, R.L. Tatham, and W.C. Black Multivariate data analysis 5th ed. 1998 Prentice Hall Upper Saddle River, New Jersey
11. D.R. Hardoon, S. Szedmak, and J. Shawe-Taylor Canonical correlation analysis: An overview with application to learning methods Neural Computation 16 2004 2639 2664 (Pubitemid 39604012)
12. J.F.R. Ilgner, C. Palm, A.G. Schutz, K. Spitzer, M. Westhofen, and T.M. Lehmann Colour texture analysis for quantitative laryngoscopy Acta Oto-Laryngologica 123 6 2003 730 734 (Pubitemid 37011614)
13. B. Jacobson, A. Jonhson, C. Grywalski, and A. Silbergleit The Voice Handicap Index (VHI): Development and validation American Journal of Speech-Language Pathology 6 1 1997 66 69 (Pubitemid 127472057)
14. T. Kohonen The self-organizing map Proceedings of the IEEE 78 9 1990 1461 1480
15. A. Konak, D.W. Coit, and A.E. Smith Multi-objective optimization using genetic algorithms: A tutorial Reliability Engineering and System Safety 91 9 2006 992 1007 (Pubitemid 43996942)
16. Kuss, M., Graepel, T. (2003). The geometry of kernel canonical correlation analysis, Technical Report 108, Max Planck Institute for Biological Cybernetics.
17. P.E.N. Lutu, and A.P. Engelbrecht A decision rule-based method for feature selection in predictive data mining Expert Systems with Applications 37 1 2010 602 609
18. R.J. Moran, R.B. Reilly, P. de Chazal, and P.D. Lacy Telephony-based voice pathology assessment using automated speech analysis IEEE Transactions on Biomedical Engineering 53 3 2006 468 477 (Pubitemid 43288824)
19. S.T. Roweis, and L.K. Saul Nonlinear dimensionality reduction by locally linear embedding Science 290 2000 2323 2326 (Pubitemid 32041578)
20. J.W. Sammon A nonlinear mapping for data structure analysis IEEE Transactions on Computers 18 5 1969 401 409
21. J. Shawe-Taylor, and N. Cristianini Kernel methods for pattern analysis 2004 Cambridge University Press Cambridge, UK
22. V.N. Vapnik Statistical learning theory 1998 Wiley New York
23. A. Verikas, A. Gelzinis, M. Bacauskiene, and V. Uloza Towards a computer-aided diagnosis system for vocal cord diseases Artificial Intelligence in Medicine 36 1 2006 71 84 (Pubitemid 43068584)
24. A. Verikas, A. Gelzinis, M. Bacauskiene, V. Uloza, and M. Kaseta Using the patient's questionnaire data to screen laryngeal disorders Computers in Biology and Medicine 39 2 2009 148 155
25. A. Verikas, A. Gelzinis, D. Valincius, M. Bacauskiene, and V. Uloza Multiple feature sets based categorization of laryngeal images Computer Methods and Programs in Biomedicine 85 3 2007 257 266 (Pubitemid 46241594)
26. A. Verikas, K. Malmqvist, M. Bacauskiene, and L. Bergman Monitoring the de-inking process through neural network-based colour image analysis Neural Computing and Applications 9 2 2000 142 151
27. Y.L. Wu, C.Y. Tang, M.K. Hor, and P.F. Wu Feature selection using genetic algorithm and cluster validation Expert Systems with Applications 38 3 2011 2727 2732
28. J. Zhu, S.R.T. Hastie, and R. Tibshirani 1-norm support vector machines S. Thrun, L.K. Saul, B. Scholkopf, Advances in neural information processing systems Vol. 16 2004 MIT Press Cambridge, MA, USA 49 56