Title
Machine Learning Analysis for Cervical Cancer Prediction, a Systematic Review of the Literature
Date Issued
01 January 2021
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
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.
Language
English
OCDE Knowledge area
Oncología Robótica, Control automático
Scopus EID
2-s2.0-85124563830
ISBN of the container
9781665440004
Conference
2021 9th E-Health and Bioengineering Conference, EHB 2021
Sources of information: Directorio de Producción Científica Scopus