Automated tooth numbering on panoramic radiographs versus cone-beam computed tomographs: A diagnostic accuracy study of a commercial artificial intelligence system
Clicks: 1
ID: 313361
2026
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
0.0
/100
1 views
0 readers
AI Quality Assessment
Not analyzed
Readership in this journal
Ranked #44 of 46 articles by views in dentomaxillofacial radiology
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Abstract Objectives To assess the diagnostic accuracy of a commercial artificial intelligence system for automated tooth numbering on panoramic radiographs and cone-beam computed tomography and to quantify case-level reliability. Methods In this retrospective single-centre diagnostic accuracy study, consecutive patients who underwent both panoramic radiography and cone-beam computed tomography in 2024 were included. The index test was automated tooth numbering generated by Diagnocat using the Fédération Dentaire Internationale numbering scheme. The reference standard was modality-specific consensus of two experienced, blinded readers. Tooth-position performance metrics with 95% confidence intervals were estimated using patient-level cluster bootstrap. Case-level reliability was defined as the proportion of examinations with completely error-free numbering across all evaluated tooth positions. Results The study analysed 178 panoramic radiographs and 174 cone-beam computed tomography examinations. Tooth-position performance was near-perfect and similar across modalities (overall accuracy 99.79% for panoramic radiographs and 99.80% for cone-beam computed tomography). At the case level, 154/178 (86.5%) panoramic radiographs and 156/174 (89.7%) cone-beam computed tomography examinations were error-free. Conclusions Despite near-perfect tooth-position metrics, approximately one in ten to one in seven examinations required at least one manual correction, demonstrating a gap between granular accuracy and case-level reliability. Advances in knowledge Reporting case-level, error-free outputs alongside tooth-position metrics provides a more clinically meaningful estimate of reliability for automated tooth numbering and supports safer workflow implementation.
| Reference Key |
openalex_W7161262935
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Nora Sultani, Natalia Kazimierczak, Zbigniew Serafin, Wojciech Kazimierczak |
| Journal | dentomaxillofacial radiology |
| Year | 2026 |
| DOI |
10.1093/dmfr/twag026
|
| URL | |
| Keywords | Keywords not found |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.