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

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

2 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojada2021 9th E-Health and Bioengineering Conference, EHB 2021
ISBN (versión digital)9781665440004
DOI
EstadoPublicada - 2021
Publicado de forma externa
Evento9th IEEE International Conference on E-Health and Bioengineering Conference, EHB 2021 - Iasi, Rumanía
Duración: 18 nov. 202119 nov. 2021

Serie de la publicación

Nombre2021 9th E-Health and Bioengineering Conference, EHB 2021

Conferencia

Conferencia9th IEEE International Conference on E-Health and Bioengineering Conference, EHB 2021
País/TerritorioRumanía
CiudadIasi
Período18/11/2119/11/21

ODS de las Naciones Unidas

Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible

  1. ODS 3: Salud y bienestar
    ODS 3: Salud y bienestar

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