Analysis of Machine Learning Model of Gynaecological Cancer Diagnosis Using Multilayer Perceptron Network

Women's health is affected with ovarian cancer, a fatal gynaecological cancer. It has become more essential to comprehend the biological and neoplastic development of ovarian cancer so as to treat patients. The fifth most common form of cancer among women globally is cancer of the ovary, which must only be identified in its most advanced stages since it has no warning symptoms. The incidence of this disease rises due to age. The epithelial type of ovarian cancer is one of several classifications of ovarian cancer. The most common cancerous ovarian tumor can be brought on by it. Women of any age may be affected by this medical condition, however women over the age of 50 are more likely to develop it. The early identification of ovarian cancer can be done using a variety of classification strategies. The categorization of cancer diseases requires using data mining as a major proportion. By reviewing numerous data mining methods, several ways were suggested for developing a classification model in an explosive field like medical, having the goal of obtaining a model with the highest classification accuracy.