Eliana Dantas Costa, Marcela Amanda Vieira, Glaucia Maria Bovi Ambrosano, Hugo Gaêta-Araujo, José Andery Carneiro, Breno Augusto Guerra Zancan, Alexander Scaranti, Alessandra Alaniz Macedo, Camila Tirapelli
{"title":"Artificial intelligence in dentistry: awareness among dentists and computer scientists.","authors":"Eliana Dantas Costa, Marcela Amanda Vieira, Glaucia Maria Bovi Ambrosano, Hugo Gaêta-Araujo, José Andery Carneiro, Breno Augusto Guerra Zancan, Alexander Scaranti, Alessandra Alaniz Macedo, Camila Tirapelli","doi":"10.1007/s11282-025-00828-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>For clinical application of artificial intelligence (AI) in dentistry, collaboration with computer scientists is necessary. This study aims to evaluate the knowledge of dentists and computer scientists regarding the utilization of AI in dentistry, especially in dentomaxillofacial radiology.</p><p><strong>Methods: </strong>610 participants (374 dentists and 236 computer scientists) took part in a survey about AI in dentistry and radiographic imaging. Response options contained Likert scale of agreement/disagreement. Descriptive analyses of agreement scores were performed using quartiles (minimum value, first quartile, median, third quartile, and maximum value). Non-parametric Mann-Whitney test was used to compare response scores between two categories (α = 5%).</p><p><strong>Results: </strong>Dentists academics had higher agreement scores for the questions: \"knowing the applications of AI in dentistry\", \"dentists taking the lead in AI research\", \"AI education should be part of teaching\", \"AI can increase the price of dental services\", \"AI can lead to errors in radiographic diagnosis\", \"AI can negatively interfere with the choice of Radiology specialty\", \"AI can cause a reduction in the employment of radiologists\", \"patient data can be hacked using AI\" (p < 0.05). Computer scientists had higher concordance scores for the questions \"having knowledge in AI\" and \"AI's potential to speed up and improve radiographic diagnosis\".</p><p><strong>Conclusion: </strong>Although dentists acknowledge the potential benefits of AI in dentistry, they remain skeptical about its use and consider it important to integrate the topic of AI into dental education curriculum. On the other hand, computer scientists confirm technical expertise in AI and recognize its potential in dentomaxillofacial radiology.</p>","PeriodicalId":56103,"journal":{"name":"Oral Radiology","volume":" ","pages":""},"PeriodicalIF":1.6000,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Oral Radiology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s11282-025-00828-z","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"DENTISTRY, ORAL SURGERY & MEDICINE","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: For clinical application of artificial intelligence (AI) in dentistry, collaboration with computer scientists is necessary. This study aims to evaluate the knowledge of dentists and computer scientists regarding the utilization of AI in dentistry, especially in dentomaxillofacial radiology.
Methods: 610 participants (374 dentists and 236 computer scientists) took part in a survey about AI in dentistry and radiographic imaging. Response options contained Likert scale of agreement/disagreement. Descriptive analyses of agreement scores were performed using quartiles (minimum value, first quartile, median, third quartile, and maximum value). Non-parametric Mann-Whitney test was used to compare response scores between two categories (α = 5%).
Results: Dentists academics had higher agreement scores for the questions: "knowing the applications of AI in dentistry", "dentists taking the lead in AI research", "AI education should be part of teaching", "AI can increase the price of dental services", "AI can lead to errors in radiographic diagnosis", "AI can negatively interfere with the choice of Radiology specialty", "AI can cause a reduction in the employment of radiologists", "patient data can be hacked using AI" (p < 0.05). Computer scientists had higher concordance scores for the questions "having knowledge in AI" and "AI's potential to speed up and improve radiographic diagnosis".
Conclusion: Although dentists acknowledge the potential benefits of AI in dentistry, they remain skeptical about its use and consider it important to integrate the topic of AI into dental education curriculum. On the other hand, computer scientists confirm technical expertise in AI and recognize its potential in dentomaxillofacial radiology.
期刊介绍:
As the official English-language journal of the Japanese Society for Oral and Maxillofacial Radiology and the Asian Academy of Oral and Maxillofacial Radiology, Oral Radiology is intended to be a forum for international collaboration in head and neck diagnostic imaging and all related fields. Oral Radiology features cutting-edge research papers, review articles, case reports, and technical notes from both the clinical and experimental fields. As membership in the Society is not a prerequisite, contributions are welcome from researchers and clinicians worldwide.