Neural Network Based diagnostic Approach for Cervical Cancer Cell stratification from Pap Smear Images

As per the recent statistics from the well-known organization WHO (World Health Organization), gynecologic cancer is fourth common cancers which affects the lives of women all over the globe. Early detection of cervical cancer, taking preventive measures, and performing primary care treatments are equally important to lower the mortality rate. Due to ambiguities in traditional diagnostic approaches, the Artificially Intelligent system-developed diagnosis comes in handy to provide a second opinion when it comes to the detection and classification of cervical cancer more quickly and efficiently. A neural network-based approach is presented in this study to classify the pap smear data at an early stage. Some important evaluation parameters such as accuracy, precision, recall, F1 score are measured to verify the efficacy of the network models.