Machine Learning Analysis for Cervical Cancer Prediction, a Systematic Review of the Literature

• Autores: Gutierrez-Espinoza, Sandy, Cabanillas-Carbonell, Michael
• Formato: artículo
• Fecha de Publicación: 2021
• Institución: Universidad Autónoma del Perú
• Repositorio: AUTONOMA-Institucional
• Lenguaje: inglés
• OAI Identifier: oai:repositorio.autonoma.edu.pe:20.500.13067/1754
• Enlace del recurso: https://hdl.handle.net/20.500.13067/1754; https://doi.org/10.1109/EHB52898.2021.9657567
• Nivel de acceso: acceso restringido
• Materia: Systematics; Asia; Machine learning; Sensitivity and specificity; Predictive models; Mathematical models; Convolutional neural networks; https://purl.org/pe-repo/ocde/ford#2.02.04

At present, cervical cancer is still the most complex issue due to the fact that people who suffer from it have a high risk of death. Therefore, it is very important to have an early diagnosis. The present study is a review of the scientific literature, which includes 50 articles from the following databases: ProQuest, IEEE Xplore, PubMed, ScienceDirect, Springer, IopScience and Scopus. Thus, showing that the research that has been developed with machine learning facilitates the control, follow-up and monitoring of the disease. The systematic review shows that the model that had the highest accuracy is Convolutional Neural Network and the most used tool is R Studio, these two factors are determinant in cervical cancer, according to the research conducted with 50 articles, where more research on this topic was recorded is the continent of Asia and specifically in the countries of India and China.