Por favor, use este identificador para citar o enlazar este ítem:
https://hdl.handle.net/20.500.12008/42878
Cómo citar
Título: | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
Autor: | Pereira-Prado, Vanesa Martins Silveira, Felipe Sicco, Estefanía Hochmann, Jimena Isiordia-Espinoza, Mario Alberto González González, Rogelio Pandiar, Deepak Bologna-Molina, Ronell |
Tipo: | Artículo |
Palabras clave: | Artificial intelligence, Deep learning, Digital image, Histopathological analysis, Machine learning, Oral squamous cell carcinoma |
Fecha de publicación: | 2023 |
Resumen: | Head and neck tumor differential diagnosis and prognosis have always been a challenge for oral pathologists due to their similarities and complexity. Artificial intelligence novel applications can function as an auxiliary tool for the objective interpretation of histomorphological digital slides. In this review, we present digital istopathological image analysis applications in oral squamous cell carcinoma. A literature search was performed in PubMed MEDLINE with the following keywords: “artificial intelligence” OR “deep learning” OR “machine learning” AND “oral squamous cell carcinoma”. Artificial intelligence has proven to be a helpful tool in histopathological image analysis of tumors and other lesions, even though it is necessary to continue researching in this area, mainly for clinical validation. |
Editorial: | MDPI |
EN: | Diagnostics, 2023, 13: 2416. |
Citación: | Pereira-Prado, V, Martins Silveira, F, Sicco, E, y otros. "Artificial intelligence for image analysis in oral squamous cell carcinoma: a review". Diagnostics. [en línea] 2023, 13: 2416. 13 h. |
ISSN: | 2075-4418 |
Aparece en las colecciones: | Publicaciones académicas y científicas 2020- - Facultad de Odontología |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | ||
---|---|---|---|---|---|
Bologna_2023_Artificial.pdf | 2,29 MB | Adobe PDF | Visualizar/Abrir |
Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons