Classification of biomedical spectra using fuzzy interquartile encoding and stochastic feature selection

Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007

Volumn , Issue , 2007, Pages 668-673

  Pizzi, Nick J ^a,b,c   Alexiuk, Mark D ^c   Pedrycz, Witold ^a,d,e  

^a IEEE

^b NATIONAL RESEARCH COUNCIL CANADA   (Canada)

^c UNIVERSITY OF MANITOBA   (Canada)

^d UNIVERSITY OF ALBERTA   (Canada)

^e Computational Intelligence ^*

Author keywords

[No Author keywords available]

Indexed keywords

CLASSIFICATION (OF INFORMATION); ENCODING (SYMBOLS); FEATURE EXTRACTION; FUZZY SETS; MAGNETIC RESONANCE; SPECTROMETERS;

BIOFLUID DATA; BIOMEDICAL SPECTRA; INTERQUARTILE RANGES;

BIOMEDICAL ENGINEERING;

EID: 34548792483     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CIDM.2007.368940     Document Type: Conference Paper

References (23)

1. B.S. Everitt, "Moments of the statistics kappa and weighted kappa," British J. Mathematical and Statistical Psychology, vol. 21, pp. 97-103, 1968.
2. J.L. Fleiss, "Measuring agreement between judges on the presence or absence of a trait," Biometrics, vol. 31, pp. 651-659, 1975.
3. J.R. Landis and G.G. Koch, "The measurements of observer agreement for categorical data,"'Biometrics, vol. 33, pp. 159-174, 1997.
4. H.C. Kraemer, Evaluating Medical Tests: Objectives and Quantitative Guidelines, Newbury Park: Sage, 1992.
5. N.J. Pizzi, "Classification of biomedical spectra using stochastic feature selection,"Neural Network World, vol. 15, no. 3, pp. 257-268, 2005.
6. J. Moody and C.J. Darken, "Fast learning networks of locally-tuned processing units," Neural Computation, vol. 1, pp. 381-294, 1989.
7. F. Girosi, T. Poggio, and B. Caprile, "Extensions of a theory of networks for approximations and learning: outliers and negative, examples," in Advances in Neural Information Processing Systems, J.E. Moody and D.S. Touretzky, Eds. San Mateo: Morgan Kaufmann Publ., 1991 pp. 750-756.
8. S. Lee and R.M. Kil, "A Gaussian potential function network with hierarchically self-organizing learning," Neural Networks, vol. 4, pp. 207-224, 1991.
9. J. Platt, "A resource-allocating network for function interpolation," Neural Computation, vol. 3, pp. 213-225, 1991.
10. E. Hartman and J.D. Keeler, "Predicting the future: advantages of semilocal units," Neural Computation, vol. 3, pp. 566-578, 1:991.
11. S.M. Weiss and C.A. Kulikowski, Computer Systems that Learn: Classification and Prediction Methods from Statistics, Neural Nets, Machine Learning and Expert Systems, San Mateo: Morgan Kaufmann Publ., 1991.
12. M.S. Srivastava and E.M. Carter, An Introduction to Applied Multivariate Statistics, New York: North-Holland, 1983.
13. N.J. Pizzi, "Bleeding predisposition assessments in tonsillectomy/ adenoidectomy patients using fuzzy interquartile encoded neural networks," Artificial Intelligence in Medicine, vol. 21, pp. 65-90, 2001.
14. N. Pizzi, "Classification of storm events using a fuzzy encoded multilayer perceptron," Proceedings of the International Joint Conference on Neural Networks, Como, Italy, July 2000, pp. 547-550.
15. N. Pizzi, L.-P. Choo, J. Mansfield, M. Jackson, W.C. Halliday, H.H. Mantsch, and R.L. Somorjai, "Neural network classification of infrared spectra of control and Alzheimer's diseased tissue," Artificial Intelligence in Medicine, vol. 1, 1995, pp 67-79.
16. L.A. Zadeh, "Outline of a new approach to the analysis of complex systems and decision processes," IEEE Transactions on Systems, Man, and Cybernetics, vol. 3, 1973, pp. 28-44.
17. B.D. Ripley, Pattern Recognition and Neural Networks, Cambridge: Cambridge University Press, 1996.
18. N.J. Pizzi and W. Pedrycz, "Predicting qualitative assessments using fuzzy aggregation," Proceedings of the North American Fuzzy Information Processing Society 'Conference, June 3.-6, Montréal, Canada, vol. MPM3, pp. 12-17, 2006.
19. A.B. Demko, N.J. Pizzi, and R.L. Somorjai, "Scopira - A System for the analysis of biomedical data," Proceedings of the IEEE Canadian Conference on Electrical and Computer Engineering, May 12-15, Winnipeg, Canada, pp. 1093-1098, 2002.
20. th ACM Conference on Object-Oriented Programming, Systems, Languages, and Applications:, October 16-20, San Diego, USA pp. 138-139, 2005.
21. nd Edition, Cambridge: MIT Press, 1998.
22. H. Friebolin, Basic one- and two-dimensional NMR spectroscopy, New York: John Wiley and Sons, 2005.
23. D.L. Pavia, G.M. Lampman, and G.S. Kriz, Introduction to Spectroscopy, Fort Worth: Harcourt Brace College Publishers, 1996.