Data fusion of several Support Vector Machine breast cancer diagnostic paradigms using a GRNN oracle

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 5434, Issue , 2004, Pages 423-430

  Land Jr , Walker H ^a   Wong, Lut ^a   McKee, Dan ^a   Masters, Timothy ^b   Anderson, Frances ^c   Sarvaiya, Sapan ^a  

^a BINGHAMTON UNIVERSITY   (United States)

^b TMAIC ^*

^c Lourdes Hospital   (United States)

Author keywords

Breast cancer; Computer aided diagnosis; GRNN Oracle; Support Vector Machines

Indexed keywords

BREAST CANCER; GENERALIZED REGRESSION NEURAL NETWORK (GRNN) ORACLE; HISTOLOGIC EXAMINATION; SUPPORT VECTOR MACHINES;

APPROXIMATION THEORY; COMPUTER AIDED DIAGNOSIS; COST ACCOUNTING; MAMMOGRAPHY; RADIOLOGY; SCREENING; SENSITIVITY ANALYSIS; TUMORS; VECTOR QUANTIZATION;

SENSOR DATA FUSION;

EID: 3843152713     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.541040     Document Type: Conference Paper

References (24)

1. J. A. Baker, P. J. Kornguth, J. Y. Lo, M. E. Williford and C. E. Floyd, Jr., "Breast cancer: prediction with artificial neural network based on BI-RADS standardized lexicon," Radiology, Vol. 196, pp. 817-22, 1995.
2. BIRADS, Breast Imaging - Reporting and Data System (BI-RADS), American College of Radiology, 1993.
3. C. J. C. Burges, "A tutorial on Support Vector Machines for pattern recognition," Data Mining and Knowledge Discovery, Vol. 2, No. 2, pp. 121-167, 1998.
4. N. Cristanini and J. Shawe-Taylor, An Introduction to Support Vector Machines and other Kernel-Based Learning Methods, Cambridge University, 2000.
5. C. E. Floyd, J. Y. Lo, A. J. Yun, D. C. Sullivan and P. J. Kornguth, "Prediction of breast cancer malignancy using an artificial neural network," Cancer, Vol. 74, pp. 2944-98, 1994.
6. D. B. Fogel, Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, IEEE Press, Piscataway, NJ, 1995.
7. D. B. Fogel, E. C. Wasson and E. M. Boughton, "Evolving neural networks for detecting breast cancer," Cancer Letters, Vol. 96, pp. 49-53, 1995.
8. D. B. Fogel, E. C. Wasson, E. M. Boughton and V. W. Porto, "A step toward computer-assisted mammography using evolutionary programming and neural networks," Cancer Letters, Vol. 119, pp. 93-97, 1997.
9. D. B. Fogel, E. C. Wasson, E. M. Boughton and V. W. Porto, "Evolving artificial neural networks for screening features from mammograms," Artificial Intelligence in Medicine, Vol. 14, pp. 317-326, 1998.
10. D. B. Fogel, E. C. Wasson, E. M. Boughton, V. W. Porto and P. J. Angeline, "Linear and neural models for classifying breast masses," IEEE Trans. Medical Imaging, Vol. 17, No. 3, pp. 485-488, 1998.
11. S. Gunn, Support Vector Machines for Classification and Regression, ISIS Technical Report, Image Speech and Intelligent Systems Group, University of Southampton, May 14, 1998.
12. S. Haykin, Neural Networks, Prentice Hall, New Jersey, 1999.
13. th World Conference on Systemics, Cybernetics and Informatics, Vol. 10, pp. 343-7, 2000.
14. W. H. Land, Jr., T. Masters and J. Y. Lo, "Application of a new evolutionary programming/adaptive boosting hybrid to breast cancer diagnosis," IEEE Congress on Evolutionary Computation Proceedings, 2000.
15. J. Y. Lo, J. A. Baker, P. J. Kornguth, J. D. Iglehart and C. E. Floyd, "Predicting breast cancer invasion with artificial neural networks on the basis of mammographic features," Radiology, Vol. 203, pp. 159-163, 1997.
16. J. Y. Lo, J. A. Baker, P. J. Kornguth and C. E. Floyd, Jr., "Effect of patient history data on the prediction of breast cancer from mammographic findings with artificial neural networks," Acad. Radiology, Vol. 6, pp. 10-15, 1999.
17. T. Masters, Advanced Algorithms for Neural Networks. John Wiley and Sons, New York, NY, 1995.
18. T. Masters and W. H. Land, Jr., "A new training method for the general regression neural network," IEEE International SMC Conference Proceedings, pp. 1990-5, 1997.
19. T. Masters, W. H. Land, Jr., and S. Maniccam, "An oracle based on the general regression neural network," SMC International Conference Proceedings, La Jolla, CA, 1998.
20. National Cancer Institute, SEER Cancer Statistics Review 1975-2000, Table I-1, Estimated New Cancer Cases and Deaths for 2003, 2003.
21. K. Price and R. Storn, "Differential Evolution," Dr. Dobb's Journal, pp. 18-24, April, 1997.
22. P. Strax, Make Sure That You Do Not Have Breast Cancer, St. Martin's, NY, 1989.
23. V. N. Vapnik, The Nature of Statistical Learning Theory, Wiley, New York, 1995.
24. V. N. Vapnik, Statistical Learning Theory, Wiley, New York, 1998.