Benefits of artificial intelligence in dental caries identification: integrative review

Authors

DOI:

https://doi.org/10.33448/rsd-v10i2.12117

Keywords:

Dental Caries; Oral Health; Diagnosis; Artificial intelligence.

Abstract

Artificial Intelligence (AI) is a software-derived mechanism that aims to mimetize human beings cognitive functions. Currently, the search for its use grows rapidly in the health sector, covering several areas, including dentistry. Dental caries is a dynamic, multifactorial and biofilm-mediated disease that results in phasic demineralization and remineralization of dental tissues. Dental caries is one of the chronic diseases that most affect people around the world. The goal of this article is to perform an integrative review of the current literature on AI in the identification of caries, emphasizing its benefits, limitations, relevance and impact. Thus, the guiding question is: how feasible can the use of a more advanced technology such as AI for the diagnosis of cavities? The research was initiated through a search in the electronic database PubMed, Web of Science, Scopus and Cochrane, using the descriptors: “dental caries”, “oral health, diagnosis” and “artificial intelligence” indexed in the period from 2009 to 2020. After the eligibility criteria, 10 articles published in English, Portuguese or Spanish were analyzed. This integrative review was able to gather recent studies that accentuate the effect of current artificial intelligence methods on oral health, showing its aid to a dentist’s work, enhancing the diagnosis’s quality, precision and ease, thus obtaining greater efficacy in the treatment.

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Published

09/02/2021

How to Cite

CABRAL, B. M. de S.; MARQUES, A. B. C.; MENEZES, M. R. A. de .; ALVES-SILVA, E. G.; SÁ, R. A. G. de .; MELO, E. L. de .; GERBI, M. E. M. de M. .; BISPO, M. E. A. . Benefits of artificial intelligence in dental caries identification: integrative review . Research, Society and Development, [S. l.], v. 10, n. 2, p. e18310212117, 2021. DOI: 10.33448/rsd-v10i2.12117. Disponível em: https://rsdjournal.org/index.php/rsd/article/view/12117. Acesso em: 22 nov. 2024.

Issue

Vol. 10 No. 2

Section

Review Article

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Copyright (c) 2021 Bianca Maria de Souza Cabral; Anna Beathriz Cariolano Marques; Maria Regina Almeida de Menezes; Esdras Gabriel Alves-Silva; Renata Araújo Gomes de Sá; Eloiza Leonardo de Melo; Marleny Elizabeth Márquez de Martínez Gerbi; Mávio Eduardo Azevedo Bispo

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