Editorial & Opinion
Reassessing the validity of AI cephalometric landmark identification: an analytical perspective on Ye et al. (2023).
| Τίτλος: | Reassessing the validity of AI cephalometric landmark identification: an analytical perspective on Ye et al. (2023). |
|---|---|
| Συγγραφείς: | Liao J; State Key Laboratory of Oral & Maxillofacial Reconstruction and Regeneration, National Clinical Research Center for Oral Diseases & Shaanxi Clinical Research Center for Oral Diseases, Department of Orthodontic, School of Stomatology, The Fourth Military Medical University, 145 West Changle Road, Xi'an, Shaanxi, China., Yu J; Chongqing University Three Gorges Hospital, No. 165, Xincheng Road, Wanzhou District, Chongqing, CN, 400044, China., Jiang F; Chongqing University Three Gorges Hospital, No. 165, Xincheng Road, Wanzhou District, Chongqing, CN, 400044, China. jfl@cqu.edu.cn. |
| Πηγή: | BMC oral health [BMC Oral Health] 2026 Aug 03; Vol. 26 (1). Date of Electronic Publication: 2026 Aug 03. |
| Τύπος έκδοσης: | Letter; Comment |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: BioMed Central Country of Publication: England NLM ID: 101088684 Publication Model: Electronic Cited Medium: Internet ISSN: 1472-6831 (Electronic) Linking ISSN: 14726831 NLM ISO Abbreviation: BMC Oral Health Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: London : BioMed Central, [2001- |
| Ιατρικοί όροι (MeSH): | Cephalometry*/methods , Image Processing, Computer-Assisted*/methods , Anatomic Landmarks*/diagnostic imaging , Artificial Intelligence*, Humans ; Reproducibility of Results ; Software |
| Περίληψη: | To provide the public and non-specialist readers with clear insight, we re-evaluate a published study claiming that artificial intelligence (AI) software performs as accurately as orthodontist experts in identifying key points on dental X-ray images. Our analysis reveals flaws in the original research methods: inconsistent image processing led to unreliable measurements, and critical details about data sources were missing. Most importantly, when we repeated the experiment with new X-ray images and protocols, over 80% of the AI's landmark identifications showed significantly higher error rates than originally reported-contradicting the claim that AI matches expert accuracy. We urge methodological rigor in future studies on AI's role in dentistry. (© 2026. The Author(s).) |
| Competing Interests: | Declarations. Ethics approval and consent to participate: This study was approved by the Ethics Review Committees of Chongqing University Affiliated Three Gorges Hospital (Approval Nos. CQTGHIRB-2024–153). The investigation was conducted in strict compliance with the pertinent guidelines and regulations. All procedures were conducted in accordance with approved guidelines, confirming that informed consent was obtained from all patients or their legal guardians. Consent to publication: Not applicable. Competing interests: The authors declare no competing interests. |
| Σχόλια: | Comment on: BMC Oral Health. 2023 Jul 8;23(1):467. doi: 10.1186/s12903-023-03188-4.. (PMID: 37422630) |
| References: | BMC Oral Health. 2023 Jul 8;23(1):467. (PMID: 37422630) |
| Grant Information: | KJZD-K202400104 Science and Technology Research Program of Chongqing Municipal Education Commission; wzstc20230409 Chongqing Wanzhou District PhD Direct-Acess Research Project |
| Contributed Indexing: | Keywords: Artifcial intelligence; Automatic digitization; Cephalometric tracings |
| Entry Date(s): | Date Created: 20260804 Date Completed: 20260804 Latest Revision: 20260813 |
| Update Code: | 20260814 |
| PubMed Central ID: | PMC13435525 |
| DOI: | 10.1186/s12903-026-08728-2 |
| PMID: | 42547861 |
| Βάση Δεδομένων: | MEDLINE |
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