Artificial Intelligence for Image Analysis in Oral Squamous Cell Carcinoma: A Review

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...

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Detalles Bibliográficos
Autores principales: Pereira-Prado, Vanesa, Martins-Silveira, Felipe, Sicco, Estafanía, Hochmann, Jimena, Isiordia-Espinoza, Mario Alberto, González, Rogelio González, Pandiar, Deepak, Bologna-Molina, Ronell
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378350/
https://www.ncbi.nlm.nih.gov/pubmed/37510160
http://dx.doi.org/10.3390/diagnostics13142416
Descripción
Sumario: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 histopathological 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.

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