2026 Volume 6 Issue 1
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Efficacy of AI in Detecting Dental Age of Pediatric Patients Visiting University Hospital: A Retrospective Study


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  1. College of Community and Global Health, University of Manitoba, Winnipeg, Canada.
  2. Internship Training Program, Riyadh Elm University, Riyadh, Saudi Arabia.
Abstract

The problems in dental age diagnosis emerged that necessitated the development of artificial intelligence which offers better computerized methods. AI systems with integrated machine learning and deep learning improve the ability of dental diagnosis from huge data sets by identifying patterns. This retrospective study had a sample size of 350 files from the pediatric division. OPGs were collected from the patient’s files and sent to the AI programmer, who utilized CNN (Convolutional Neural Network) to identify the patients’ gender and dental age. In the first phase, the CNN was trained to correctly identify the patient’s age and gender using 20 OPGs. Later in the second phase, the remaining 330 OPGs were added to the CNN, and its accuracy was tested. Inclusion criteria included pediatric patients without any systemic diseases or dental trauma and OPG’s without any defects within past 5 years. Findings showed an accuracy of 69% in detecting the patients’ dental age and gender. AI can be used in forensic dentistry to detect patients’ dental age and gender if trained properly. A major challenge in using AI is the need to teach it to achieve desired results.


How to cite this article
Vancouver
Ansari SH, Almusailem RA, Alhussaini MB, Almajed HI, Alshehri RM. Efficacy of AI in Detecting Dental Age of Pediatric Patients Visiting University Hospital: A Retrospective Study. Turk J Public Health Dent. 2026;6(1):1-11. https://doi.org/10.51847/GwpatkrrLs
APA
Ansari, S. H., Almusailem, R. A., Alhussaini, M. B., Almajed, H. I., & Alshehri, R. M. (2026). Efficacy of AI in Detecting Dental Age of Pediatric Patients Visiting University Hospital: A Retrospective Study. Turkish Journal of Public Health Dentistry, 6(1), 1-11. https://doi.org/10.51847/GwpatkrrLs
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Issue 2 Volume 6 - 2026