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Title: Artificial Intelligence for Image Analysis in Oral Squamous Cell Carcinoma: A Review
Authors: Pereira Prado, Vanesa
Martins Silveira, Felipe
Sicco, Estafanía
Hochmann, Jimena
Isiordia Espinoza, Mario Alberto
González González, Rogelio
Pandiar, Deepak
Bologna Molina, Ronell Eduardo
Keywords: artificial intelligence
deep learning
digital image
histopathological analysis
machine learning
oral squamous cell carcinoma
Issue Date: Jul-2023
Publisher: MDPI
Citation: : Pereira-Prado, V.; Martins-Silveira, F.; Sicco, E.; Hochmann, J.; Isiordia-Espinoza, M.A.; González, R.G.; Pandiar, D.; Bologna-Molina, R. Artificial Intelligence for Image Analysis in Oral Squamous Cell Carcinoma: A Review. Diagnostics 2023, 13, 2416. diagnostics13142416
Series/Report no.: Diagnostics;2023, 13, 2416
Abstract: 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.
Description: Artículo
ISBN: diagnostics13142416
ISSN: 2075-4418
Appears in Collections:3209 Artículos

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