LIMITATIONS OF ARTIFICIAL INTELLIGENCE IN DENTAL AESTHETIC PLANNING: A SCOPING REVIEW AND INDIVIDUALIZED CRANIOMETRIC PROPOSAL FOR DEFINING MAXILLARY CENTRAL INCISOR WIDTH
DOI:
https://doi.org/10.47820/recima21.v7i2.7253Keywords:
Artificial Intelligence, digital dentistry, Dental Aesthetics; Smile; Mouth Rehabilitation.Abstract
Objective: To map and analyze the available scientific evidence on the limitations of Artificial Intelligence in dental aesthetic planning, with emphasis on the definition of the width of the maxillary central incisor. Materials and methods: This is a scoping review conducted in accordance with the guidelines of the Joanna Briggs Institute. Studies published between 2022 and 2025 that addressed the use of digital technologies and Artificial Intelligence applied to dental aesthetic planning were included. The selection included methodological, observational, clinical and diagnostic studies, with no language restrictions. The data were extracted, organized and synthesized in a descriptive way, considering methodological, technological, aesthetic characteristics and the methodological quality of the studies. Results: Ten studies were included, predominantly developed in China, with samples ranging from large databases to clinical studies with a small number of cases. Wide adoption of digital technologies was observed, with recurrent use of Artificial Intelligence associated with CAD-CAM flows, Digital Smile Design, dental segmentation, radiographic diagnosis and automated design of restorations. Despite the satisfactory technical performance and the low risk of methodological bias, the studies showed limitations related to aesthetic individualization, with a predominance of the use of standardized models and population means, especially in the definition of the width of the maxillary central incisor. Final considerations: Artificial Intelligence has high potential to optimize dental aesthetic planning; however, its limitations regarding personalization reinforce the need to incorporate individualized craniometric parameters and clinical judgment into algorithms, aiming at a more accurate, humanized and evidence-based planning.
Downloads
References
ABDELHAFEZ, Marwa; AFIA, AbdelRahman; SHAALAN, Omar. Artificial Intelligence Versus Conventional Methods in Digital Smile Designing: An Accuracy Study. Journal of Esthetic and Restorative Dentistry, 2025. DOI: https://doi.org/10.1111/jerd.70075
ABUSHEHAB, Abdallah et al. Midface skeletal sexual dimorphism: lessons learned from advanced three-dimensional imaging in the white population. Plastic and Reconstructive Surgery–Global Open, v. 12, n. 10, p. e6215, 2024. DOI: https://doi.org/10.1097/GOX.0000000000006215
ADEL, Samar M. et al. Clinical audit of an artificial intelligence (AI) empowered smile simulation system: a prospective clinical trial. Scientific Reports, v. 14, n. 1, p. 19385, 2024. DOI: https://doi.org/10.1038/s41598-024-69314-6
BAE, Juyoung et al. CrownGen: Patient-customized Crown Generation via Point Diffusion Model. arXiv preprint arXiv:2512.21890, 2025.
BARROSO, C. E. O. F. et al. Artificial Intelligence in dentistry: Advances and applications in modern clinical practice. São Paulo: Seven Editora, 2024, p. 237-255. DOI: https://doi.org/10.56238/sevened2024.006-021
BARTOLO, Daniela et al. The golden ratio as an ecological affordance leading to aesthetic attractiveness. PsyCh Journal, v. 11, n. 5, p. 729-740, 2022. DOI: https://doi.org/10.1002/pchj.505
BUDURU, Smaranda et al. Perceptions in digital smile design: Assessing laypeople and dental professionals’ preferences using an Artificial-intelligence-based application. Dentistry Journal, v. 12, n. 4, p. 104, 2024. DOI: https://doi.org/10.3390/dj12040104
CEYLAN, Gülsüm et al. Evaluating the facial esthetic outcomes of digital smile designs generated by artificial intelligence and dental professionals. Applied Sciences, v. 13, n. 15, p. 9001, 2023. DOI: https://doi.org/10.3390/app13159001
CHEN, Du et al. Precise tooth design using deep learning-based templates. Journal of Dentistry, v. 144, p. 104971, 2024. DOI: https://doi.org/10.1016/j.jdent.2024.104971
CHEUNG, Kwantong et al. Establishment of a 3D esthetic analysis workflow on 3D virtual patient and preliminary evaluation. BMC Oral Health, v. 24, n. 1, p. 328, 2024. DOI: https://doi.org/10.1186/s12903-024-04085-0
DE ARAÚJO, Eduarda Gomes Onofre et al. A inteligência artificial no ensino da Odontologia: uma análise bibliométrica. Journal of Health Informatics, v. 16, n. Especial, 2024. DOI: https://doi.org/10.59681/2175-4411.v16.iEspecial.2024.1301
DE MORAES, Érica Brandão et al. Protocolos de Revisão. Online Brazilian Journal of Nursing, v. 21, n. Suppl 1, 2022. DOI: https://doi.org/10.17665/1676-4285.20226585
GONÇALVES, Sergio Eduardo de Paiva; TRIBST, João Paulo Mendes; FARDIM, Karolina Aparecida Castilho. Scientific writing with artificial intelligence: key considerations and alerts. Braz. dent. sci, p. 1-5, 2023.
GOPFERT, Isabela Marthes; RIVERA, Gustavo. Proporção áurea e harmonia de sorriso em alunos de graduação da Universidade Católica de Brasília. Oral Sciences, p. 43-47, 2012.
GRANJEIRO, José Mauro et al. The future of scientific writing: AI tools, benefits, and ethical implications. Brazilian Dental Journal, v. 36, p. e25-6471, 2025. DOI: https://doi.org/10.1590/0103-644020256471
JARDIM, Jerusa Jobim et al. Inteligência artificial aplicada aos exames de imagem odontológicos: uma revisão da literatura. Revista da Faculdade de Odontologia de Porto Alegre, v. 64, p. e128781-e128781, 2023. DOI: https://doi.org/10.22456/2177-0018.128781
JUNIOR, Howard Lopes Ribeiro. (Digital) Science in Dentistry: Challenges, Innovations, and the Path Forward. Brazilian Journal of Dentistry Oral Radiology, v. 4, n. 1, p. bjd52-bjd52, 2025. DOI: https://doi.org/10.52600/2965-8837.bjdor.2025.4.bjd52
JUNIOR, Joao Jose Dantas Santos et al. A aplicação da inteligência artificial no planejamento do sorriso: precisão, eficiência e impacto na experiência do paciente. Revista Multidisciplinar Integrada-REMI, v. 6, n. 1, 2025. DOI: https://doi.org/10.61164/xpjae212
PAGE, O. N. Preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) checklist. Br J Sports Med, v. 1001, p. 58, 2024.
RODRIGUES, Jonas de Almeida; SANTOS, Henrique Pereira dos. Is artificial intelligence really a future trend in health care?. Ciência odontológica brasileira, São Paulo, v. 24, n. 3, p. 1-4, 2021. DOI: https://doi.org/10.14295/bds.2021.v24i3.3108
SALES, Weslley Barbosa et al. Métodos, ferramentas e aplicações da metanálise em revisões: uma revisão sistemática. Revista de Ciências da Saúde Nova Esperança, v. 22, n. 3, p. 439-450, 2024. DOI: https://doi.org/10.17695/rcsne.vol22.n3.p439-450
SAVEGNAGO, Gleica et al. Inteligência artificial na odontologia: uma revisão narrativa de literatura. Revista da Faculdade de Odontologia-UPF, v. 29, n. 1, 2024. DOI: https://doi.org/10.5335/rfo.v29i1.15733
TANIKAWA, C.; ZERE, E.; TAKADA, K. Sexual dimorphism in the facial morphology of adult humans: a three-dimensional analysis. Homo, v. 67, n. 1, p. 23-49, 2016. DOI: https://doi.org/10.1016/j.jchb.2015.10.001
WANG, Yin-Chih Chelsea et al. Artificial Intelligence to Assess Dental Findings from Panoramic Radiographs--A Multinational Study. arXiv preprint arXiv:2502.10277, 2025.
XIE, Bing-ying et al. Morphological comparison between artificial intelligence-driven and manual CAD design in single tooth restoration: a preliminary study. BMC Oral Health, v. 25, n. 1, p. 1633, 2025. DOI: https://doi.org/10.1186/s12903-025-07004-z
XIONG, Huimin et al. TFormer: 3D tooth segmentation in mesh scans with geometry guided transformer. arXiv preprint arXiv:2210.16627, 2022.
Downloads
Published
Issue
Section
Categories
License
Copyright (c) 2026 RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218
This work is licensed under a Creative Commons Attribution 4.0 International License.
Os direitos autorais dos artigos/resenhas/TCCs publicados pertecem à revista RECIMA21, e seguem o padrão Creative Commons (CC BY 4.0), permitindo a cópia ou reprodução, desde que cite a fonte e respeite os direitos dos autores e contenham menção aos mesmos nos créditos. Toda e qualquer obra publicada na revista, seu conteúdo é de responsabilidade dos autores, cabendo a RECIMA21 apenas ser o veículo de divulgação, seguindo os padrões nacionais e internacionais de publicação.
