Evidence map›Paper›PMID 41729260›Full record

ArticleInternational journal of legal medicine2026

Dental age estimation: a scoping review comparing the manual application of the Demirjian method and artificial intelligence modalities.

Stephanie Baylis, Joanna F Dipnall, Richard Bassed

Abstract readComparative StudyScoping Review
In one paragraph

Article in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Stephanie BaylisDepartment of Forensic Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia. stephanie1baylis@gmail.com.ORCID http://orcid.org/0000-0001-8697-0996
Joanna F DipnallSchool of Public Health and Preventive Medicine, Monash University , Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0001-7543-0687
Richard BassedDepartment of Forensic Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC, Australia.ORCID http://orcid.org/0000-0001-5473-055X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The investigation of the viability using Artificial intelligence (AI) compared to the Demirjian method in dental age estimation is growing. This scoping review looked at how AI-assisted dental age estimation models compare to the Demirjian method and their usefulness to general and forensic dentists. Searches were conducted in Medline, Embase, Global Health, Scopus, Social Science Premium Collection, CENTRAL-Cochrane Library Central Register of Controlled Trials, and NZLII-New Zealand Legal Information Institute. Google and Google Scholar searches were also undertaken to identify any grey material. Twenty-two articles were included in this review, organised into three groups to assist comparisons i.e., stage allocation, stage allocation prior to AI model application, and use of the Demirjian method on study samples prior to applying AI models. Comparisons were difficult due to considerable variation in samples, dental features used, metrics, AI modelling, unstated regression methods, and reporting. Of the twenty-two studies included in this review, nine showed similar performance between experts manually applying Demirjian stages with/out scoring and AI models, four reported the AI models were better, two reported AI models were worse, four reported mixed results, one did not recommend either, while two did not report a comparison. Lessons learned from the traditional methods of dental age estimation have been ignored in many respects and important real-world requirements for legal and clinical applications are being overlooked.

Indexed as

Age Determination by TeethArtificial IntelligenceHumansAdult vs minorBlack boxDemirjian stagesHuman rightsLegal consequences

Identifiers

PMID41729260
PMCPMC13161306

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.