Predicting the Risk Factors of Endometrial Cancer using Data Mining

Data mining act as an imperative part for uncovering new idea in healthcare organization which is supportive for all the parties related with medical field. This paper analyses the effectiveness of Data mining technique in healthcare domain. Cancer is one among the foremost crisis today, diagnosing cancer in earlier period is still challenging for doctors. Detection of hereditary and ecological aspect is very essential in developing novel methods to perceive and stop cancer. Endometrial cancer is one of the most general feminine gynaecologic malignancy, is naturally a curable disease. It is the most wide-ranging of the entire cancers and the main reason for the cancer fatality in women worldwide. This paper also presents an study of the risk factors related with endometrial cancer by means of association rule mining. Here we applied Apriori algorithm to uncover the associations. Women who are extensively heavy weight, hypertension and more estrogens level are increased risk of certain cancers. Heavy weight, hypertension, and more estrogens level were drastically related with an increased risk of endometrial cancer.