Deep Learning Approach to Cervical Cancer Classification

Cervical cancer is caused in the vast majority of cases by the human papillomavirus through sexual contact and requires a specific analysis with specialised equipment and health professionals to be detected. In this work, we perform an exhaustive analysis of the classifier systems developed in recent years and develop our own classifier through the evaluation of multiple combinations and the detailed adjustment of the system’s hyperparameters. The classifiers developed (for two and four classes following the Bethesda System nomenclature) are evaluated in depth and compared with the works published in the last five years. The results determine an accuracy close to 98\% for the four-class classifier (with no false positives for the negative class) and 100\% for the two-class classifier.