Classification of Cervical Cancer Detection Using Machine Learning Algorithms

Cervical cancer remains an important reason of deaths worldwide because effective access to cervical screening methods is a big challenge. Cervical cancer is one of the most deadly diseases in the world among women. It is caused by long term infection in skin cells and mucous membrane cells of the genital area. The worrisome aspect of this cancer lies in the fact that it does not show any symptoms when it starts occurring. Women in the world are suffering from many diseases among those diseases Cervical Cancer is also mentioned globally. Every year many cancer more comfortable life. Cervical cancer is one such disease, considered to be fourth among the most common types of cancer in women around the world. There are many factors that increase the risk of cervical cancer, such as age and use of hormonal contraceptives. Early detection of cervical cancer helps to raise recovery rates and reduce death rates. In our proposed work, we used Machine Learning algorithms to find a model capable of diagnosing cervical cancer with high accuracy and sensitivity. The cervical cancer risk factor dataset was used to construct the classification model through a voting method that combines three classifiers: Decision Tree, ANN, K-N Neighbor and Random Forest.