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State of the art and prospects for artificial intelligence in orthognathic surgery: A systematic review with meta-analysis

dc.contributor.authorTakeshita, Wilton Mitsunari [UNESP]
dc.contributor.authorSilva, Thaísa Pinheiro
dc.contributor.authorde Souza, Laura Luiza Trindade
dc.contributor.authorTenorio, Josceli Maria
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionUniversidade Estadual de Campinas (UNICAMP)
dc.contributor.institutionUniversidade Federal de Sergipe (UFS)
dc.contributor.institutionFederal Institute of São Paulo
dc.date.accessioned2025-04-29T20:11:18Z
dc.date.issued2024-12-01
dc.description.abstractObjective: To present a systematic review of the state of the art regarding clinical applications, main features, and outcomes of artificial intelligence (AI) in orthognathic surgery. Methods: The PICOS strategy was performed on a systematic review (SR) to answer the following question: “What are the state of the art, characteristics and outcomes of applications with artificial intelligence for orthognathic surgery?” After registering in PROSPERO (CRD42021270789) a systematic search was performed in the databases: PubMed (including MedLine), Scopus, Embase, LILACS, MEDLINE EBSCOHOST and Cochrane Library. 195 studies were selected, after screening titles and abstracts, of which thirteen manuscripts were included in the qualitative analysis and six in the quantitative analysis. The treatment effects were plotted in a Forest-plot. JBI questionnaire for observational studies was used to asses the risk of bias. The quality of the SR evidence was assessed using the GRADE tool. Results: AI studies on 2D cephalometry for orthognathic surgery, the Tau2 = 0.00, Chi2 = 3.78, p = 1.00 and I² of 0 %, indicating low heterogeneity, AI did not differ statistically from control (p = 0.79). AI studies in the diagnosis of the decision of whether or not to perform orthognathic surgery showed heterogeneity, and therefore meta-analysis was not peformed. Conclusion: The outcome of AI is similar to the control group, with a low degree of bias, highlighting its potential for use in various applications.en
dc.description.affiliationDepartment of Diagnosis and Surgery São Paulo State University (Unesp) School of Dentistry, São Paulo
dc.description.affiliationDepartment of Oral Diagnosis Division of Oral Radiology Piracicaba Dental School University of Campinas (UNICAMP), Sao Paulo
dc.description.affiliationDepartment of Dentistry Federal University of Sergipe, Sergipe
dc.description.affiliationDepartment of Information technology and health Federal Institute of São Paulo, São Paulo
dc.description.affiliationUnespDepartment of Diagnosis and Surgery São Paulo State University (Unesp) School of Dentistry, São Paulo
dc.identifierhttp://dx.doi.org/10.1016/j.jormas.2024.101787
dc.identifier.citationJournal of Stomatology, Oral and Maxillofacial Surgery, v. 125, n. 6, 2024.
dc.identifier.doi10.1016/j.jormas.2024.101787
dc.identifier.issn2468-7855
dc.identifier.scopus2-s2.0-85184740944
dc.identifier.urihttps://hdl.handle.net/11449/308118
dc.language.isoeng
dc.relation.ispartofJournal of Stomatology, Oral and Maxillofacial Surgery
dc.sourceScopus
dc.subjectArtificial intelligence
dc.subjectClinical decision support systems
dc.subjectMachine learning
dc.subjectOrthognathic surgery
dc.titleState of the art and prospects for artificial intelligence in orthognathic surgery: A systematic review with meta-analysisen
dc.typeArtigopt
dspace.entity.typePublication
unesp.author.orcid0000-0002-7485-0206[2]

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