Analysis of Ovarian Cancer Using Back-Propagation Algorithm with Gradient-Descent Models

Most Women is at danger ovarian cancer; about 90 percent of women who get ovarian cancer are above 40 years of age, with the greatest number of ovarian cancers taking place at the age of 60 years and above. Ovarian cancer arises from the ovary indicates growth of cancer. Each year, almost 20,000 women in the United States get ovarian cancer and also, ovarian cancer is the eighth most common cancer and the fifth leading cause of cancer death. More than 91% of ovarian cancers are known as "epithelial tumors" which start from the outer surface epithelium, the thin tissue forming the outer layer of a body's surface and lining the alimentary canal and other hollow structures of the ovary. The intention of this study is to observe the performance of the Back propagation techniques using Gradient-Descent Model over Genetic Algorithm on the analysis of ovarian cancer using proven ovarian dataset fig 2. Ovarian cancer [2] accounts for the most caused cancer diagnoses among women. We propose a comparison between Genetic Algorithm and BPA in ANN [1] for preoperative guess of enmity in ovarian tumors.