Accuracy in diagnosing caries in young permanent molars using interproximal radiographic imaging and validation by artificial intelligence
There was excellent inter-examiner agreement in evaluating caries diagnosis for the teeth assessed. The AI-based method proposed in this study showed good performance and proved effective in recognizing caries lesions in radiographic images. <b>Key words:</b>Dental caries, Artificial intelligence, Radiography, Bitewing, Child.
Authors
- Richard Niederman (ORCID: https://orcid.org/0000-0001-6674-1774)
- André L. M. Santos (ORCID: https://orcid.org/0000-0001-6661-5970)
- Márcia Maria Fonseca da Silveira (ORCID: https://orcid.org/0000-0002-2611-5661)
- Débora Heloísa Silva de Brito (ORCID: https://orcid.org/0000-0001-6123-6453)
- Thaysa Gomes Ferreira Tenório dos Santos (ORCID: https://orcid.org/0000-0002-9331-7669)
- Samylla Glória de Araújo Costa (ORCID: https://orcid.org/0000-0003-2530-6463)
- Bruno Fernandes (ORCID: https://orcid.org/0000-0002-6001-3925)
- I. Silva (ORCID: https://orcid.org/0009-0009-9745-1230)
- Nathália Regina Cauás da Silva
- Aronita Rosenblatt (ORCID: https://orcid.org/0000-0003-4606-6374)
- Cláudia Cristina Brayner de Oliveira Mota
Institutions
- York University (US)
- Universidade de Pernambuco (BR)
Publication Details
- Journal
- Journal of Clinical and Experimental Dentistry
- Published
- 2025-01-01
- DOI
- https://doi.org/10.4317/jced.62396
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Universidade de Pernambuco