Cervical Cancer Analysis Using Deep Learning Classification Model

Cervical cancer is a vital cancer disease for women, which needs to be predicted using various technical tools. Although different computational learning models have been used to test the disease in many cases, their performance needs to improve according to appropriate methods. Thus, this paper proposes developing an aggregated deep-learning model to perform on the cervical cancer disease dataset. The proposed model creates predefined data from the original dataset and utilizes it for various methods, including convolutional, recurrent, artificial neural networks, and long short-term memory. Those methods are evaluated based on their approaches using the cervical cancer dataset. The proposed model is demonstrated on the cervical cancer disease dataset and analyzed in terms of individual and comparative performance. The performance of the proposed model is also improved by more than 95% on each evaluation parameter.