Application of deep learning to the classification of uterine cervical squamous epithelial lesion from colposcopy images combined with HPV types

The aim of the present study was to explore the feasibility of using deep learning, such as artificial intelligence (AI), to classify cervical squamous epithelial lesions (SILs) from colposcopy images combined with human papilloma virus (HPV) types. Among 330 patients who underwent colposcopy and bi...

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Detalles Bibliográficos
Autores principales: Miyagi, Yasunari, Takehara, Kazuhiro, Nagayasu, Yoko, Miyake, Takahito
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2020
Materias:
Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956417/
https://www.ncbi.nlm.nih.gov/pubmed/31966086
http://dx.doi.org/10.3892/ol.2019.11214

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6956417/
https://www.ncbi.nlm.nih.gov/pubmed/31966086
http://dx.doi.org/10.3892/ol.2019.11214

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