Prediction of Cervical Cancer using Multilayer Perceptron Algorithm

Abstract

The fourth most frequent illness-related cause of death in women is cervical malignant growth. Cervical cancer is associated with the presence of the human papillomavirus (HPV). Early detection has made cervical cancer preventable, which has decreased overall impact of the disease. Due to the high expense of routine exams, a lack of awareness, and limited access to medical facilities, women do not participate in enough screening programs in underdeveloped countries. This way, each patient is expected to be at extremely high risk. There are numerous threat factors that can lead to the growth of cervical cancer. As a result, the datasets will be checked for cervical cancer by using a variety of data analytics tools, including machine learning and deep learning algorithms. The classification of normal and abnormal cervical data is done by performing a quick overview of how cervical cancer works and is detected.