Artificial intelligence for image analysis in oral squamous cell carcinoma: a review
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.
| 2023 | |
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Artificial intelligence Deep learning Digital image Histopathological analysis Machine learning Oral squamous cell carcinoma |
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| Inglés | |
| Universidad de la República | |
| COLIBRI | |
| https://hdl.handle.net/20.500.12008/42878 | |
| Acceso abierto | |
| Licencia Creative Commons Atribución (CC - By 4.0) |
| _version_ | 1872865337796460544 |
|---|---|
| author | Pereira-Prado, Vanesa |
| author2 | Silveira, Felipe Martins Sicco, Estefanía Hochmann Valls, Jimena Isiordia-Espinoza, Mario Alberto González González, Rogelio Pandiar, Deepak Bologna-Molina, Ronell |
| author2_role | author author author author author author author |
| author_facet | Pereira-Prado, Vanesa Silveira, Felipe Martins Sicco, Estefanía Hochmann Valls, Jimena Isiordia-Espinoza, Mario Alberto González González, Rogelio Pandiar, Deepak Bologna-Molina, Ronell |
| author_role | author |
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| collection | COLIBRI |
| dc.contributor.filiacion.none.fl_str_mv | Pereira-Prado Vanesa, Universidad de la República (Uruguay). Facultad de Odontología. Silveira, Felipe Martins Universidad de la República (Uruguay). Facultad de Odontología Sicco Estefanía, Universidad de la República (Uruguay). Facultad de Odontología Hochmann Valls Jimena, Universidad de la República (Uruguay). Facultad de Odontología Isiordia-Espinoza Mario Alberto, Universidad de Guadalajara (Mexico). González González Rogelio, Universidad Juárez del Estado de Durango (México). Pandiar Deepak, Saveetha Dental College And Hospitals (India). Bologna-Molina Ronell, Universidad de la República (Uruguay). Facultad de Odontología |
| dc.creator.none.fl_str_mv | Pereira-Prado, Vanesa Silveira, Felipe Martins Sicco, Estefanía Hochmann Valls, Jimena Isiordia-Espinoza, Mario Alberto González González, Rogelio Pandiar, Deepak Bologna-Molina, Ronell |
| dc.date.accessioned.none.fl_str_mv | 2024-03-04T15:25:08Z |
| dc.date.available.none.fl_str_mv | 2024-03-04T15:25:08Z |
| dc.date.issued.none.fl_str_mv | 2023 |
| dc.description.abstract.none.fl_txt_mv | 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. |
| dc.format.extent.es.fl_str_mv | 13 h. |
| dc.format.mimetype.es.fl_str_mv | application/pdf |
| dc.identifier.citation.es.fl_str_mv | Pereira-Prado, V, 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. |
| dc.identifier.doi.none.fl_str_mv | 10.3390/diagnostics13142416 |
| dc.identifier.issn.none.fl_str_mv | 2075-4418 |
| dc.identifier.uri.none.fl_str_mv | https://hdl.handle.net/20.500.12008/42878 |
| dc.language.iso.none.fl_str_mv | en_US eng |
| dc.publisher.es.fl_str_mv | MDPI |
| dc.relation.none.fl_str_mv | Diagnostics, 2023, 13: 2416. |
| dc.rights.license.none.fl_str_mv | Licencia Creative Commons Atribución (CC - By 4.0) |
| dc.rights.none.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.source.none.fl_str_mv | reponame:COLIBRI instname:Universidad de la República instacron:Universidad de la República |
| dc.subject.es.fl_str_mv | Artificial intelligence Deep learning Digital image Histopathological analysis Machine learning Oral squamous cell carcinoma |
| dc.title.none.fl_str_mv | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
| dc.type.es.fl_str_mv | Artículo |
| dc.type.none.fl_str_mv | info:eu-repo/semantics/article |
| dc.type.version.none.fl_str_mv | info:eu-repo/semantics/publishedVersion |
| description | 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. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | COLIBRI_f7bf04a23ac2f040f13b0ae5eae0341a |
| identifier_str_mv | Pereira-Prado, V, 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. 2075-4418 10.3390/diagnostics13142416 |
| instacron_str | Universidad de la República |
| institution | Universidad de la República |
| instname_str | Universidad de la República |
| language | eng |
| language_invalid_str_mv | en_US |
| network_acronym_str | COLIBRI |
| network_name_str | COLIBRI |
| oai_identifier_str | oai:colibri.udelar.edu.uy:20.500.12008/42878 |
| publishDate | 2023 |
| reponame_str | COLIBRI |
| repository.mail.fl_str_mv | karina.camps@seciu.edu.uy |
| repository.name.fl_str_mv | COLIBRI - Universidad de la República |
| repository_id_str | 4771 |
| rights_invalid_str_mv | Licencia Creative Commons Atribución (CC - By 4.0) |
| spelling | Pereira-Prado Vanesa, Universidad de la República (Uruguay). Facultad de Odontología.Silveira, Felipe Martins Universidad de la República (Uruguay). Facultad de OdontologíaSicco Estefanía, Universidad de la República (Uruguay). Facultad de OdontologíaHochmann Valls Jimena, Universidad de la República (Uruguay). Facultad de OdontologíaIsiordia-Espinoza Mario Alberto, Universidad de Guadalajara (Mexico).González González Rogelio, Universidad Juárez del Estado de Durango (México).Pandiar Deepak, Saveetha Dental College And Hospitals (India).Bologna-Molina Ronell, Universidad de la República (Uruguay). Facultad de Odontología2024-03-04T15:25:08Z2024-03-04T15:25:08Z2023Pereira-Prado, V, 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.2075-4418https://hdl.handle.net/20.500.12008/4287810.3390/diagnostics13142416Head 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.Submitted by Farias Verónica (verofariasblundell@gmail.com) on 2024-03-04T15:21:55Z No. of bitstreams: 2 license_rdf: 24251 bytes, checksum: 71ed42ef0a0b648670f707320be37b90 (MD5) Bologna_2023_Artificial.pdf: 2348623 bytes, checksum: 15bdc0468c3a211495f674efc4ae6d1f (MD5)Made available in DSpace by Seroubian Mabel (mabel.seroubian@seciu.edu.uy) on 2024-03-04T15:25:08Z (GMT). No. of bitstreams: 2 license_rdf: 24251 bytes, checksum: 71ed42ef0a0b648670f707320be37b90 (MD5) Bologna_2023_Artificial.pdf: 2348623 bytes, checksum: 15bdc0468c3a211495f674efc4ae6d1f (MD5) Previous issue date: 202313 h.application/pdfen_USengMDPIDiagnostics, 2023, 13: 2416.Las obras depositadas en el Repositorio se rigen por la Ordenanza de los Derechos de la Propiedad Intelectual de la Universidad de la República.(Res. Nº 91 de C.D.C. de 8/III/1994 – D.O. 7/IV/1994) y por la Ordenanza del Repositorio Abierto de la Universidad de la República (Res. Nº 16 de C.D.C. de 07/10/2014)info:eu-repo/semantics/openAccessLicencia Creative Commons Atribución (CC - By 4.0)Artificial intelligenceDeep learningDigital imageHistopathological analysisMachine learningOral squamous cell carcinomaArtificial intelligence for image analysis in oral squamous cell carcinoma: a reviewArtículoinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionreponame:COLIBRIinstname:Universidad de la Repúblicainstacron:Universidad de la RepúblicaPereira-Prado, VanesaSilveira, Felipe MartinsSicco, EstefaníaHochmann Valls, JimenaIsiordia-Espinoza, Mario AlbertoGonzález González, RogelioPandiar, DeepakBologna-Molina, RonellLICENSElicense.txtlicense.txttext/plain; charset=utf-84267http://localhost:8080/xmlui/bitstream/20.500.12008/42878/5/license.txt6429389a7df7277b72b7924fdc7d47a9MD55CC-LICENSElicense_urllicense_urltext/plain; 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públicahttps://udelar.edu.uy/https://www.colibri.udelar.edu.uy/oai/requestkarina.camps@seciu.edu.uyUruguayopendoar:47712026-03-20T16:26:52COLIBRI - Universidad de la Repúblicafalse |
| spellingShingle | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review Pereira-Prado, Vanesa Artificial intelligence Deep learning Digital image Histopathological analysis Machine learning Oral squamous cell carcinoma |
| status_str | publishedVersion |
| title | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
| title_full | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
| title_fullStr | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
| title_full_unstemmed | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
| title_short | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
| title_sort | Artificial intelligence for image analysis in oral squamous cell carcinoma: a review |
| topic | Artificial intelligence Deep learning Digital image Histopathological analysis Machine learning Oral squamous cell carcinoma |
| url | https://hdl.handle.net/20.500.12008/42878 |
