Digital and artificial intelligence-assisted cephalometric training effectively enhanced students’ landmarking accuracy in preclinical orthodontic education
Digital cephalometric training effectively enhances students' landmarking accuracy in preclinical orthodontic education. AI-assisted cephalometry has the potential to minimize performance disparities among students with varying levels of clinical experience. Owing to the real-time feedback and self-directed learning features of digital tools, these technologies serve as valuable supplements to instructor-led training, potentially reducing educators' workload and accelerating skill acquisition in novice orthodontic students. However, these preliminary findings require further multicenter validation and long-term educational assessments while also considering the ethical implications of these technologies.
Authors
- Jiayu Lin
- Robert K. Yu (ORCID: https://orcid.org/0000-0002-7873-195X)
- Manyi Wang (ORCID: https://orcid.org/0000-0002-6324-5502)
- Chufeng Liu (ORCID: https://orcid.org/0000-0002-3995-0148)
- Jingtao Dai (ORCID: https://orcid.org/0000-0003-0013-0676)
- Zhen-gui Liao
- Hong Yang
Institutions
- Southern Medical University (CN)
Publication Details
- Journal
- BMC Oral Health
- Published
- 2025-04-24
- DOI
- https://doi.org/10.1186/s12903-025-05978-4
- Citations
- 6
- Primary Topic
- Dental Research and COVID-19
- Type
- article
- Field-Weighted Citation Impact
- 16.95
Funders
- Southern Medical University
- Chinese Stomatological Association
- Division of Graduate Education