Diagnosing Cervical Cancer Using Machine Learning Methods

Pre-diagnosis of any kind of cancer type has critical impact on person's life. According to World Health Organization Cervical cancer is still one of the most common gynecologic cancers in the world that affects women life. if medical experts focus on early diagnosis of the disease which is detecting symptomatic patients as early as possible, patients will have the best chance for successful treatment since Cervical Cancer is preventable. When cancer treatment is delayed, mortality rate decreases, and treatment becomes more complicated and expensive. Currently, systems based on Artificial Intelligence are used for decision making Machine learning techniques let automated detection of cervical cancer run more quickly and efficiently. In this study a novel ensemble approach is presented to predict the risk of cervical cancer by developing hybrid machine learning model. Multiple performance measurements such as Accuracy, precision score, recall score, and F1 are performed to evaluate the novel model. The results indicate that the proposed novel model can be effectively used to pre diagnosis of Cervical cancer with accuracy 97%.