Keywords
Panoramic radiography
Diagnostic imaging
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Abstract
Objective: To evaluate the effectiveness and applicability of a Deep Learning–based Artificial Intelligence (AI) tool as a screening and diagnostic support instrument in panoramic radiographs. Methods: This is a cross-sectional observational study conducted using a convenience sample of 40 digital radiographs with previously issued technical reports (reference standard). The images were processed using an AI platform (DIO Inteligência Odontológica), and the generated reports were compared with the original reports through a confusion matrix and qualitative analysis to calculate accuracy, sensitivity, and specificity. Results: The analysis of 1,452 observation points indicated an overall accuracy of 67.9%, with a sensitivity of 68.8% and a specificity of 67.5%. Qualitative analysis revealed limitations of the AI in spatial interpretation (impacted teeth and dental migration), leading to sequencing errors. Conversely, the tool demonstrated a high capacity for detecting subclinical findings, such as incipient caries and subtle bone rarefactions. Conclusion: The evaluated AI system demonstrated moderate performance, not replacing professional diagnosis but functioning effectively as a screening and alert tool to optimize clinical workflow under human supervision.
References
ARAÚJO LCP, et al. A eficácia da radiologia na precisão diagnóstica na prática odontológica: uma revisão sistemática. Revista Contemporânea, 2025; 5(5): 1-20.
BARBOSA MES, et al. Uso da inteligência artificial na odontologia. Revista Multidisciplinar Integrada - REMI, 2025; 5: 1-12.
BONNY T, et al. Contemporary Role and Applications of Artificial Intelligence in Dentistry. F1000Research, 2023; 12: 1179.
CARVALHO VG, et al. Impacto da inteligência artificial na odontologia: revisão integrativa da literatura. In: Interfaces atuais da odontologia: conexões entre tecnologia, educação e humanização na saúde bucal. IMEA: João Pessoa-PB, 2025; p14-47.
DE ANGELIS F, et al. Artificial Intelligence: A New Diagnostic Software in Dentistry: A Preliminary Performance Diagnostic Study. Int. J. Environ. Res. Public Health, 2022; 19: 1728.
DHOPTE A, BAGDE H. Smart Smile: Revolutionizing Dentistry With Artificial Intelligence. Cureus, 2023; 15(6): e41227.
FLETCHER RH, et al. Epidemiologia Clínica: Elementos Essenciais. 5. ed. Porto Alegre: Artmed, 2014.
GIRI D, DONGR P. Artificial Intelligence - Future trend in Oral Diagnosis and Radiology. International Journal of Current Science Research and Review, 2022; 5(9): 1-5.
HEO MS, et al. Artificial intelligence in oral and maxillofacial radiology: what is currently possible?. Dentomaxillofac Radiol, 2021; 50: 20200375.
JARDIM JJ, et al. Inteligência artificial aplicada aos exames de imagem odontológicos – uma revisão da literatura. Revista da Faculdade de Odontologia de Porto Alegre, 2023; 64: 1-28.
MAIA DC, et al. Os desafios e impactos da inteligência artificial na radiologia: uma revisão sistemática. Revista de Ciências Biológicas e da Saúde, 2025; 15: 63-71.
MARTINS CA, et al. Análise da inteligência artificial no diagnóstico de lesões cariosas em radiografia interproximal: uma revisão de literatura. Brazilian Journal of Implantology and Health Sciences, 2025; 7(10): 751-769.
MENDES APS, MACEDO PTS. Uso da inteligência artificial na radiologia odontológica: revisão sistemática. JNT Facit Business and Technology Journal, 2025; 2(68): 400-412.
OLIVEIRA LPS, et al. Inteligência artificial no diagnóstico de lesões cariosas: revisão integrativa. Revista Odontológica de Araçatuba, 2025; 46(1): 32-38.
PEREIRA CAB, et al. Inteligência artificial aplicada aos exames de imagem: impactos na tomada de decisão clínica e na atuação multiprofissional em saúde. Revista de Geopolítica, 2026; 17(2): e1484.
PRADOS-PRIVADO M, et al. Dental Images Recognition Technology and Applications: A Literature Review. Appl. Sci., 2020; 10: 2856.
PRASANNAM RP, et al. Artificial intelligence in dental practice: a review. International Journal of Community Medicine and Public Health, 2023; 10(5): 1955-1960.
PUTRA RH, et al. Current applications and development of artificial intelligence for digital dental radiography. Dentomaxillofac Radiol, 2022; 51: 20210197.
SAVEGNAGO G, et al. Inteligência artificial na odontologia: uma revisão narrativa de literatura. Revista da Faculdade de Odontologia - UPF, 2024; 29(1): 1-18.
SCHWENDICKE F, et al. Artificial Intelligence in Dentistry: Chances and Challenges. Journal of Dental Research, 2020; 99(7): 769-774.
SILVA TP, et al. Estado da arte da Inteligência Artificial (IA) na radiologia odontológica: revisão sistemática. Archives of Health Investigation, 2021; 10(7): 1084-1089.
THURZO A, et al. Where Is the Artificial Intelligence Applied in Dentistry? Systematic Review and Literature Analysis. Healthcare, 2022; 10: 1269.