The knowledge, experience, and attitude on artificial intelligence-assisted cephalometric analysis: Survey of orthodontists and orthodontic students
Open accessAbstract
Introduction Artificial intelligence (AI) developed rapidly in orthodontics, and AI-based cephalometric applications have been adopted. This study aimed to assess AI-assisted cephalometric technologies related knowledge, experience, and attitude among orthodontists and orthodontic students; describe their subject view of the applications and related technologies in orthodontics; and identify associated factors. Methods An online cross-sectional survey based on a professional tool (www.wjx.cn) was performed from October 11-17, 2022. Participants were recruited with a purposive and snowball sampling approach. Data was collected and analyzed with descriptive statistics, chi-square tests, and multivariable generalized estimating equations. Results Four hundred eighty valid questionnaires were collected and analyzed; 68.8% of the respondents agreed that AI-based cephalometric applications would replace manual and semiautomatic approaches. Practitioners using AI-assisted applications (87.5%) spent less time in cephalometric analysis than the other groups using other approaches, and 349 (72.7%) respondents considered AI-based applications could assist in obtaining more accurate analysis results. Lectures and training programs (56.0%) were the main sources of respondents' knowledge about AI. Knowledge level was associated with experience in AI-related clinical or scientific projects (P <0.001). Most respondents (88.8%) were interested in future AI applications in orthodontics. Conclusions Respondents are optimistic about the future of AI in orthodontics. AI-assisted cephalometric applications were believed to make clinical diagnostic analysis more convenient and straightforward for practitioners and even replace manual and semiautomatic approaches. The education and promotion of AI should be strengthened to elevate orthodontists' understanding.
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“many studies reported an expected increase in overall efficiency [38, 41, 44, 45, 55, 56, 62, 67, 77–80] as a facilitating factor, a reduction in overall workload [82–84] or improved time management [52, 66].”
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- Authors
- Lin, L., Tang, B., Cao, L., Yan, J., Zhao, T., Hua, F., & He, H.
- Affiliations
- Wuhan University (CN)
- University of Manchester (GB)
- Corresponding author
- Hua, Fang
- He, Hong
- Venue
- American Journal of Orthodontics and Dentofacial Orthopedics
- Publisher
- Elsevier BV
- Published
- 2023-10
- Volume
- 164
- Issue
- 4
- Pages
- e97-e105
- ISSN
- 0889-5406 (ISSN-L)
- OpenAlex
- W4385689613
- Cited by
- 26
- References
- 47
- Citations by year
- 2026: 9 · 2025: 10 · 2024: 5 · 2023: 2
- FWCI
- 6.77
- Type
- journal article
- Language
- en
- Open access
- Licence
- Locations
- American Journal of Orthodontics and Dentofacial Orthopedics (publishedVersion)
- PubMed (publishedVersion)
- Research Explorer (The University of Manchester) (publishedVersion, other-oa)
- Funders
- Wuhan University (2021ZG328)
- Chinese Stomatological Association (COS-B2021-08)
- Topics
- Health Sciences › Dentistry › Orthodontics › Orthodontics and Dentofacial Orthopedics
- Health Sciences › Dentistry › Oral Surgery › Dental Radiography and Imaging
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- artificial intelligence, orthodontists, knowledge and attitudes, clinical experience, artificial intelligence adoption, orthodontic education
- MeSH terms
- Orthodontists, Artificial Intelligence, Cross-Sectional Studies, Humans, Health Knowledge, Attitudes, Practice, Surveys and Questionnaires, Students
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