Cargando…
Comparison of machine and deep learning for the classification of cervical cancer based on cervicography images
Cervical cancer is the second most common cancer in women worldwide with a mortality rate of 60%. Cervical cancer begins with no overt signs and has a long latent period, making early detection through regular checkups vitally immportant. In this study, we compare the performance of two different mo...
Autores principales: | Park, Ye Rang, Kim, Young Jae, Ju, Woong, Nam, Kyehyun, Kim, Soonyung, Kim, Kwang Gi |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8352876/ https://www.ncbi.nlm.nih.gov/pubmed/34373589 http://dx.doi.org/10.1038/s41598-021-95748-3 |
Ejemplares similares
-
The performance of tele-cervicography for detection of preinvasive and invasive disease of the uterine cervix as an adjunctive test to Pap smears
por: Nam, Kyehyun, et al.
Publicado: (2016) -
RGB Channel Superposition Algorithm with Acetowhite Mask Images in a Cervical Cancer Classification Deep Learning Model
por: Kim, Yoon Ji, et al.
Publicado: (2022) -
Development and validation of novel digitalized cervicography system
por: Kim, Soo-Nyung, et al.
Publicado: (2016) -
Digital cervicography and cold coagulation for cervical cancer screening in Nigeria
por: Adebamowo, Clement, et al.
Publicado: (2012) -
Comparison between Deep Learning and Conventional Machine Learning in Classifying Iliofemoral Deep Venous Thrombosis upon CT Venography
por: Hwang, Jung Han, et al.
Publicado: (2022)