Staging of cervical cancer with soft computing

IEEE Transactions on Biomedical Engineering

Volumn 47, Issue 7, 2000, Pages 934-940

  Mitra, Pabitra ^a   Mitra, Sushmita ^a   Pal, Sankar K ^a  

^a INDIAN STATISTICAL INSTITUTE   (India)

Author keywords

Classification; Genetic algorithms; ID3; Knowledge based networks; Medical decision support system; Modular neural networks; Rough sets; Rule extraction

Indexed keywords

DECISION SUPPORT SYSTEMS; DIAGNOSIS; GENETIC ALGORITHMS; GYNECOLOGY; KNOWLEDGE BASED SYSTEMS; NEURAL NETWORKS; OBSTETRICS; ONCOLOGY;

CERVICAL CANCER; INTERACTIVE DICHOTOMIZER ALGORITHM; SOFT COMPUTING;

BIOMEDICAL ENGINEERING;

ALGORITHM; ARTICLE; CANCER STAGING; COMPUTER NETWORK; COMPUTER PROGRAM; DATA ANALYSIS; MEDICAL DECISION MAKING; UTERINE CERVIX CANCER;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOMEDICAL ENGINEERING; COMPUTERS; DECISION SUPPORT TECHNIQUES; FEMALE; HUMANS; NEOPLASM STAGING; UTERINE CERVICAL NEOPLASMS;

EID: 0033932032     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/10.846688     Document Type: Article

References (16)

1. L. A. Brinton, "Epidemiology of cervical cancer - Overview, the epidemiology of cervical cancer and human papilloma virus," IACR, vol. 119, pp. 4-23, 1992.
2. K. Jayant, R. S. Rao, B. M. Nene, and P. S. Dale, "Improved stage at diagnosis of cervical cancer with increased cancer awareness in a rural Indian population," Int. J. Cancer, vol. 63, pp. 161-163, 1995.
3. "National Cancer registry programme," ICMR, Chennai, India, Biennial Rep., 1988-89.
4. P. Szolovits, R. S. Patil, and W. B. Schwatrz, "Artificial intelligence in medical diagnosis," Ann. Internal Med., vol. 108, pp. 80-87, 1988.
5. L. A. Zadeh, "Fuzzy logic, neural networks, and soft computing," Commun. ACM. vol. 37, pp. 77-84, 1994.
6. S. K. Pal and S. Mitra, Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing. New York: Wiley, 1999.
7. C. Perneel, J. M. Themlin, J. M. Renders, and M. Acheroy, "Optimization of fuzzy expert systems using genetic algorithms and neural networks," IEEE Trans. Fuzzy Syst., vol. 3, pp. 300-312, 〈month?〉 1995.
8. K. Tumer, N. Ramanujam, J. Ghosh, and R. Richards-Kortum, "Spectroscopic detection of cervical pre-cancer through radial basis function networks,"IEEE Trans. Biomed. Eng., vol. 45, pp. 953-962, Aug. 1998.
9. G. G. Towell and J. W. Shavlik, "Knowledge-based artificial neural networks," Artif. Intell., vol. 70, pp. 119-165, 1994.
10. Z. Pawlak, Rough Sets, Theoretical Aspects of Reasoning About Data. Dordrecht: Kluwer Academic, 1991.
11. S. K. Pal and A. Skowron, Eds., Rough Fuzzy Hybridization: New Trends in Decision Making. Singapore: Springer Verlag, 1999.
12. Y. H. Pao, Adaptive Pattern Recognition and Neural Networks. Reading, MA: Addison-Wesley, 1989.
13. B. M. Happel and J. J. Murre, "Design and evolution of modular neural network architectures," Neural Networks, vol. 7, pp. 985-1004, 1994.
14. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison-Wesley, 1989.
15. M. Banerjee, S. Mitra, and S. K. Pal, "Rough fuzzy MLP: Knowledge encoding and classification," IEEE Trans. Neural Networks, vol. 9, pp. 1203-1216, June 1998.
16. J. R. Quinlan, C4.5, Programs for Machine Learning. San Diego, CA: Morgan Kauffman, 1993.