Evidence map›Paper›PMID 41413889›Full record

ArticleBMC oral health2025

Evaluating a cost-effective, web-based AI platform for lateral cephalometric analysis: a comparative in-silico study.

Omar Ali Kamel Eldeeb, Yomna Mohamed Yacout, Hassan Mohamed Abouelkheir, Yousria Salah ElDin Gaweesh, Noha M Elkersh

Abstract readComparative Study
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Omar Ali Kamel EldeebMaster's candidate, Department of Oral Medicine, Periodontology, Oral Diagnosis and Oral Radiology, Faculty of dentistry, Alexandria University, Alexandria, Egypt.
Yomna Mohamed YacoutDepartment of Orthodontics, Faculty of Dentistry, Alexandria University, Alexandria, Egypt.
Hassan Mohamed AbouelkheirDepartment of Oral Medicine, Periodontology, Oral Diagnosis and Oral Radiology, Faculty of Dentistry, Alexandria University, Alexandria, Egypt.
Yousria Salah ElDin GaweeshDepartment of Oral Medicine, Periodontology, Oral Diagnosis and Oral Radiology, Faculty of Dentistry, Alexandria University, Alexandria, Egypt.
Noha M ElkershDepartment of Oral Medicine, Periodontology, Oral Diagnosis and Oral Radiology, Faculty of Dentistry, Alexandria University, Alexandria, Egypt. noha.elkersh@alexu.edu.eg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite the current popularity of artificial intelligence (AI)- assisted cephalometric analysis, its cost precludes its widespread use in low-income countries. Free alternatives are available but mostly lack rigorous validation. Thus, this study aimed to assess the precision of AI-assisted tracing using a freely available web-based platform (WebCeph) (Artificial Intelligence Orthodontic & Orthognathic Cloud Platform, South Korea) by comparing it with the gold standard (manual tracing on OnyxCeph software) (Image Instruments, Chemnitz, Germany). It was also compared with commercially available AI-assisted tracing software (Carestream) (Carestream Dental LLC, Atlanta, GA, USA). MATERIALS AND

methodsLateral cephalometric radiographs of 57 randomly selected patients were included in this study. The radiographs were obtained from the archives of the Radiology unit, Faculty of Dentistry, Alexandria University. Three lateral cephalometric analysis methods were used. OnyxCeph3™ software was considered the gold standard (Control group), the web-based, WebCeph™ platform, was used as an online AI-based cephalometric analysis platform and set as test group 1, and the desktop-based, Carestream imaging software V8, was used for AI cephalometric analysis and set as test group 2. Skeletal and dental measurements of Steiner and Tweed analyses that were generated using the three methods were compared.

resultsStatistically significant differences were detected between the three methods in 11 out of the 18 cephalometric measurements. Notably, in Steiner analysis, the Max1-NA angle was significantly larger in WebCeph than Onyxceph and Carestream by 2.38° and 3.41°, respectively. The Mand1-NB angle was significantly larger in Onyxceph than Carestream and WebCeph by 3.07° and 2.01°, respectively. In Tweed analysis, all the measured variables were significantly different between the three methods, except the AFH. Particularly, the values of IMPA, POr-OcP, PFH, and facial height index were significantly different in Carestream than both Onyxceph and WebCeph. Fewer and smaller discrepancies were detected between WebCeph and the manual gold standard than those detected between Carestream and the manual gold standard.

conclusionsThe freely available AI web-based platform, WebCeph, performed comparably to manual tracing, and outperformed the commercially available AI desktop-based software, Carestream, in several key parameters, making it a viable tool for resource-limited settings.

Indexed as

Artificial IntelligenceCephalometryInternetComputer SimulationCost-Benefit AnalysisFemaleHumansImage Processing, Computer-AssistedIntelligent SystemsMaleSoftwareArtificial intelligenceLateral cephalogramSteiner analysisTweed analysis

Identifiers

PMID41413889
PMCPMC12766963

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.