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dc.contributor.authorPereira Prado, Vanesa-
dc.contributor.authorMartins Silveira, Felipe-
dc.contributor.authorSicco, Estafanía-
dc.contributor.authorHochmann, Jimena-
dc.contributor.authorIsiordia Espinoza, Mario Alberto-
dc.contributor.authorGonzález González, Rogelio-
dc.contributor.authorPandiar, Deepak-
dc.contributor.authorBologna Molina, Ronell Eduardo-
dc.identifier.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. diagnostics13142416es, en
dc.identifier.isbn diagnostics13142416-
dc.descriptionArtículoes, en
dc.description.abstractHead 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, en
dc.language.isoenes, en
dc.publisherMDPIes, en
dc.relation.ispartofseriesDiagnostics;2023, 13, 2416-
dc.subjectartificial intelligencees, en
dc.subjectdeep learninges, en
dc.subjectdigital imagees, en
dc.subjecthistopathological analysises, en
dc.subjectmachine learninges, en
dc.subjectoral squamous cell carcinomaes, en
dc.titleArtificial Intelligence for Image Analysis in Oral Squamous Cell Carcinoma: A Reviewes, en
dc.typeArticlees, en
Appears in Collections:3209 Artículos

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