Luiz Roberto Augusto Noro, Maria Cristina Manzanares Céspedes
{"title":"Artificial intelligence and oral photography: an approach to the epidemiology of dental caries.","authors":"Luiz Roberto Augusto Noro, Maria Cristina Manzanares Céspedes","doi":"10.11606/s1518-8787.2025059006910","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Dental caries is an important public health issue due to its high prevalence around the world, its impact on people's quality of life, and the existence of effective methods to control and prevent it. This study aims to find the state of the art regarding the diagnosis of caries with the use of artificial intelligence in the scientific literature, which could represent future advances in its use in oral health epidemiology.</p><p><strong>Methods: </strong>A scoping review was carried out based on a search strategy on the main health databases that found 1,439 articles by descriptors or keywords related to caries, diagnosis, and artificial intelligence.</p><p><strong>Results: </strong>After analysis, 17 scientific articles composed the final sample. Of these, 94.1% are quite recent, published from 2020 onward. Although the articles were based on a clinical perspective, their objectives, results, and conclusions signal the possible effectiveness of artificial intelligence as a strategic tool for epidemiology. Frontal, lateral, and occlusal photographs served to diagnose caries on all sides of the teeth.</p><p><strong>Conclusion: </strong>It is essential to invest in alternatives related to artificial intelligence and oral photography to replace traditional epidemiological surveys, which would enable the full development of oral health surveillance.</p>","PeriodicalId":21230,"journal":{"name":"Revista de saude publica","volume":"59 ","pages":"e53"},"PeriodicalIF":2.4000,"publicationDate":"2026-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12713531/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Revista de saude publica","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.11606/s1518-8787.2025059006910","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Objective: Dental caries is an important public health issue due to its high prevalence around the world, its impact on people's quality of life, and the existence of effective methods to control and prevent it. This study aims to find the state of the art regarding the diagnosis of caries with the use of artificial intelligence in the scientific literature, which could represent future advances in its use in oral health epidemiology.
Methods: A scoping review was carried out based on a search strategy on the main health databases that found 1,439 articles by descriptors or keywords related to caries, diagnosis, and artificial intelligence.
Results: After analysis, 17 scientific articles composed the final sample. Of these, 94.1% are quite recent, published from 2020 onward. Although the articles were based on a clinical perspective, their objectives, results, and conclusions signal the possible effectiveness of artificial intelligence as a strategic tool for epidemiology. Frontal, lateral, and occlusal photographs served to diagnose caries on all sides of the teeth.
Conclusion: It is essential to invest in alternatives related to artificial intelligence and oral photography to replace traditional epidemiological surveys, which would enable the full development of oral health surveillance.