Title :
Ovarian cancer prognosis and soft computing
Author_Institution :
Sch. of Math. & Inf. Sci., Coventry Univ., UK
Abstract :
This paper highlights seven applications of various methods in soft computing to the task of ovarian cancer prognosis. Soft computing is described as well as its constituents. The ovarian cancer data is described. The task involves building a series of prognostic classifiers to carry out time-step prognosis. The results from the seven methods described are compared briefly, and also are compared with statistical multilinear regression analysis.
Keywords :
biological organs; cancer; gynaecology; medical computing; statistical analysis; gynaecological cancer; ovarian cancer prognosis; prognostic classifiers series; soft computing; statistical multilinear regression analysis; time-step prognosis; Artificial neural networks; Cancer; Computer networks; Diseases; Feedforward neural networks; Fuzzy logic; Fuzzy sets; Genetic algorithms; Neural networks; Regression analysis;
Conference_Titel :
Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint
Print_ISBN :
0-7803-7612-9
DOI :
10.1109/IEMBS.2002.1134387
