ArticleFrontiers in dental medicine2026
Validation of the Dental Age app for automated dental age estimation using Demirjian's method.
Article in Frontiers in dental medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Exploring the association between skeletal malocclusions and dental maturity in German children and adolescents : A retrospective cross-sectional study.Journal of orofacial orthopedics = Fortschritte der Kieferorthopadie : Organ/official journal Deutsche Gesellschaft fur Kieferorthopadie · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Dental age estimation is an essential tool in clinical, orthodontic, and forensic contexts, with Demirjian's method (1973) being one of the most widely used worldwide. Recently, digital resources have been developed to automate this process, such as the Dental Age application (Crescendo Treinamentos Avançados, Brazil), available in English for iOS and Android. The aim of this study was to validate the Dental Age app for dental age estimation using Demirjian's method, by assessing its accuracy in relation to chronological age and its agreement with the manual approach. Methods: This retrospective cross-sectional study used a convenience sample of 63 panoramic radiographs of healthy children treated at a university pediatric dentistry clinic in Nova Friburgo, RJ, Brazil, aged 3-16 years. The mineralization stages of the seven left mandibular teeth were classified by an experienced orthodontist. Dental age was estimated in two ways: (I) manual Demirjian's method and (II) automated analysis using the Dental Age app. Chronological age was used as the reference. Performance metrics (Mean Absolute Error-MAE, Mean Squared Error-MSE, Root Mean Squared Error-RMSE, and coefficient of determination- Results: The sample included 25 boys (40%) with a mean chronological age of 12.4 years (range: 8.2-15.9) and 38 girls (60%) with a mean chronological age of 12.8 years (range: 7.5-15.9). The Dental Age app showed a MAE of 0.92 years, RMSE of 1.29, and Conclusion: The Dental Age app demonstrated equivalent performance to the traditional method, presenting itself as a practical and reliable tool for dental age estimation in children and adolescents.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.