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 original | Inglés |
|---|---|
| Título de la publicación alojada | 2021 9th E-Health and Bioengineering Conference, EHB 2021 |
| ISBN (versión digital) | 9781665440004 |
| DOI | |
| Estado | Publicada - 2021 |
| Publicado de forma externa | Sí |
| Evento | 9th IEEE International Conference on E-Health and Bioengineering Conference, EHB 2021 - Iasi, Rumanía Duración: 18 nov. 2021 → 19 nov. 2021 |
Serie de la publicación
| Nombre | 2021 9th E-Health and Bioengineering Conference, EHB 2021 |
|---|
Conferencia
| Conferencia | 9th IEEE International Conference on E-Health and Bioengineering Conference, EHB 2021 |
|---|---|
| País/Territorio | Rumanía |
| Ciudad | Iasi |
| Período | 18/11/21 → 19/11/21 |
ODS de las Naciones Unidas
Este resultado contribuye a los siguientes Objetivos de Desarrollo Sostenible
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ODS 3: Salud y bienestar
Huella
Profundice en los temas de investigación de 'Machine Learning Analysis for Cervical Cancer Prediction, a Systematic Review of the Literature'. En conjunto forman una huella única.Citar esto
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