Effectiveness of artificial intelligence in the treatment of dental caries: An integrative review

Authors

DOI:

https://doi.org/10.33448/rsd-v10i4.13083

Keywords:

Dental Caries; Artificial Intelligence; Dentistry.

Abstract

The artificial intelligence (AI) is a branch of computing science which uses similar algorithms as a specialist before making any decisions and solving complex issues. In health, the benefits occur from data generation to improve management processes, identifying better treatments and helping in prevention and disclosure early-stage diseases. The purpose of this survey was to perform an integrative review on modern literature about AI to early diagnosis caries injuries, considering the benefits, limitations and impact in society and oral health. An integrative review had been done by searching 6 English scientific articles using on-line databases: PubMed, Cochrane, Scopus and Web of Science, using keywords such as: dental caries, artificial intelligence and dentistry. Moreover, other 6 articles were found by manual research indexed from 2016 to 2020, which worked with case report titled in vitro and in vivo. After eligibility criteria, 12 articles fully published in English and Portuguese were analyzed. The studies have shown that several modern methods of artificial intelligence offered exactness, ease of diagnosis and treatment effectiveness. Nevertheless, this technique has been through an experimental phase, it is required enhancement to reduce mistakes and misconception caused by this system.

References

Angelino, K., Edlund, D.A., Shah, P., et al. (2017). Near-Infrared Imaging for Detecting Caries and Structural Deformities in Teeth. (5):2300107. doi: 10.1109 / JTEHM.2017.2695194.

Araújo, A. A., et al. (2020). Métodos de detecção e diagnóstico de cárie: uma revisão narrativa. Research, Society and Development. 9(10), e36291110019. doi: 10.33448/rsd-v9i10.10019.

Cruz, A. I., Gomes, Neto, M. M., Lima, W. T. S., Silva, W. A., Hora, S. L. (2020). Novos métodos de diagnóstico para detecção da cárie dental - Revisão integrativa. Research, Society and Development. 9(10, e7209109160. doi: 10.33448/rsd-v9i10.9160

Dündar, A., Çiftçi, M. E., İşman, Ö., Aktan, A. M. (2020). In vivo performance of nearinfrared light transillumination for dentine proximal caries detection in permanent teeth. The Saudi dental journal, 32(4), 187–193. https://doi: 10.1016/j.sdentj.2019.08.007

Endres, M. G., Hillen, F., Salloumis, M., Sedaghat, A. R., Niehues, S. M., Quatela, O., et al. (2020). Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs. Diagnostics (Basel). 10(6): 430. https://doi: 10.3390/diagnostics10060430.

Hung, M., Voss, M. W., Rosales, M. N., Li, W., Su, W., Xu, J., et al. (2019). Application of machine learning for diagnostic prediction of root caries. Web of Science, 36: 395–404. https://doi: 10.1111/ger.12432

Leão, Filho. J. C. B., de Souza, T. R. (2017). Métodos de detecção de cárie: do tradicional às novas tecnologias de emprego clínico. Revista de Odontologia da Universidade Cidade de São Paulo, 23(3), 253-265. Recuperado de http://publicacoes.unicid.edu.br/index.php/revistadaodontologia/article/view/385

Lee, J. H., Kim, D. H., Jeong, S. N., Choi, S. H. (2018). Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm. 77: 106-111. https://doi: 10.1016/j.jdent.2018.07.015

Pereira, A. S., et al. (2018). Metodologia da Pesquisa Cientifica. (e-book). Santa Maria. Ed. UAB/NTE/UFSM.

Pingali, L. (2019). Personal oral health consultant using multimodal machine detection and learning with smartphones and cloud. (10). https://doi: 10.1109/ CCEM48484.2019.000-3

Shan, T., Tay, F. R., Gu, L. (2020). Application of Artificial Intelligence in Dentistry. SAGE Journal, 100(3):232-244. https://doi: 10.1177/0022034520969115

Schwendicke, F., Golla, T., Dreher, M., Krois, J. (2019). Convolutional neural networks for dental image diagnostics: A scoping review. 91: 103226. https://doi: 10.1016/j.jdent.2019.103226

Published

17/04/2021

How to Cite

CARVALHO, D. K. de .; COSTA, M. L. L. .; ALVES-SILVA, E. G. .; MELO, E. L. de .; GERBI, M. E. M. de M. .; BISPO, M. E. A. .; SÁ, R. A. G. de .; MENEZES, M. R. A. de . Effectiveness of artificial intelligence in the treatment of dental caries: An integrative review. Research, Society and Development, [S. l.], v. 10, n. 4, p. e43210413083, 2021. DOI: 10.33448/rsd-v10i4.13083. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/13083. Acesso em: 19 apr. 2024.

Issue

Section

Health Sciences