PREDICTING CERVICAL CANCER USING MULTIPLE MACHINE LEARNING TECHNIQUES

Now a day, cervical cancer is the most common and prevailing gynecologic malignancies. Cervical cancer is the third type of cancer after breast and lungs cancer in women. Although its highly preventable disease provided early screening is done so as to minimize the global burden. However, due to unawareness, ignorance, lack of medical facilities and expensive procedures in developing countries, the vulnerable patient populations cannot afford to undergo examination regularly. A novel ensemble approach is presented in this paper to predict the risk of cervical cancer using machine learning approach. In this paper, we proposed a prediction model that can predict with accuracy the presence or absence of cervical cancer from as many as 35 possible risk features recorded for each woman. As per the results, the proposed approach is accurate, scalable and practical