A Survey of Deep Learning Assisted Prediction of Cervical Cancer: A Comparative Approach N. Indumathi 1 and Dr. D. Shanthi 2 1-2 PSNA College of Engineering and Technology, Department of CSE, Dindigul, India Email: indhujegan1996@gmail.com, dshan71@gmail.com Abstract—There are more referrals and unneeded diagnostic tests as a result of current approaches for cervical cancer prediction. The purpose of this study was to create and assess a more reliable cervical cancer prediction model. According to the World Health Organization, cervical cancer is the fourth most common disease in women, accounting for 7.9 percent of all malignancies in women. Machine learning (ML) and deep learning (DL) are being used by more and more people and businesses to evaluate vast volumes of data and generate useful insights. Metaheuristics in the category of evolutionary algorithms include genetic algorithms (GAs). In large, challenging search areas, GAs can find the optimal or nearly optimal solutions, and they are frequently employed for search and optimization. For outcome prediction, statistical models, different kinds of medical imaging, and machine learning have all been utilized with encouraging outcomes. Machine learning has proven to be more effective than traditional statistical models at navigating the complexities of massive amounts of data and identifying prognostic indicators. However, the shortcomings of prediction studies and prediction models, such as over fitting, lack of interpretability, insufficient data, and simplification, suggest that further work is required to improve clinical outcome prediction and make it more accurate, reliable, and useful for clinical usage. Index Terms— Statistical Models, Prognostic Indicators, Machine Learning and Deep Learning, genetic algorithms. I. INTRODUCTION One of the most common medical diseases affecting women worldwide, particularly in developing countries, is cervical illness. According to WHO statistics, 270 000 women died from cervical malignant growth in 2012, with 90% of these deaths occurring in low- and middle-income countries. In 2012, 445,000 new cases were recorded (around 84 percent of the new cases around the world). The pace of these passings was expected to increase by 25% in the absence of even the slightest hint of short activity. Early symptoms of cervical illness can include a regular monthly cycle, excessive bleeding, random bleeding, or spotting. The Pap (Papanicolaou) smear is a practically painless, quick, and simple cervical malignant growth screening test. Cells from a woman's cervix are gathered and spread out on a microscope slide during a pelvic exam for evaluation. The passing rate for cervical disease has decreased by 90% as a result of pap tests, and the number of cases has decreased by 60% to 90%. This test has a few flaws, including a weak clinical component, bad patient consistency, a frivolous conclusion, insufficient follow-up treatment, and carelessness on the part of the professionals in charge of it because it is so exhausting. There have been fewer fatalities from cervix malignant growth with the introduction of the pap smear test and the HPV vaccination to prevent infections in younger women, that is, those who are Grenze ID: 01.GIJET.9.1.28 © Grenze Scientific Society, 2023 Grenze International Journal of Engineering and Technology, Jan Issue