Abstract: Ovarian cancer is a cancer that forms in or on an ovary. It results in abnormal cells that have the ability to invade or spread to other parts of the body. Earlier diagnosis of Ovarian Cancer saves enormous lives, failing which may lead to other severe problems causing sudden fatal end. Its cure rate and prediction depends mainly on the early detection and diagnosis of the disease. The ovarian cancer can be detected in the early stage by the statistical approach to interpret the change in levels in women's blood of the protein CA125, which is linked to ovarian cancer. Now the computer aided method combined with the medical field to provide the better treatment for the cancer patient by using data mining techniques. This is mainly used to predict the levels of the ovarian cancer. This can be predicted with the help of dataset which contains the gene names which affect the ovary and the sample tested values. Thus the aim of the paper is to provide the optimal solution to predict the ovarian cancer.
Keywords: ovarian cancer, optimal feature selection, predicting levels.
Title: Ovarian Cancer Prediction using Bacterial Foraging Optimization
Author: Narmada.G.S, Pavithra.C.J, Prema.P, T. Guhan
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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