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TRUVACE RECORD VERSION
record: TRV-2026-2834
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:32:47.214924Z
status: published
lens: trace
sector: health
headline: Integrating Artificial Intelligence into Orthodontic Education: A Systematic Review and Meta-Analysis of Clinical Teaching Application
dek: Background/Objectives: Artificial intelligence (AI) is rapidly emerging as a transformative force in healthcare education, including orthodontics. This systematic review and meta-analysis aimed to evaluate the integration of AI into orthodontic training programs, focusing on its effectiveness in improving diagnostic accuracy, learner engagement, and the perceived quality of AI-generated educational content. Materials and Methods: A comprehensive literature search was conducted across PubMed, Scopus, Web of Scien…
gain_title: A systematic review of seven studies with 1,101 participants found AI-assisted cephalometry training improved orthodontic students' landmarking accuracy, and pooled ChatGPT content quality scored 3.69 on the Global Quality Scale (two studies).
problem_title: A systematic review of seven orthodontic education studies found 87.8% of North American programs lacked formal AI seminars and faculty cited high costs (89.3%) and lack of technical knowledge (94.7%).
trace_subject: AI integration in orthodontic education
gain_reading: A systematic review of seven studies with 1,101 participants found AI-assisted cephalometry training improved orthodontic students' landmarking accuracy, and pooled ChatGPT content quality scored 3.69 on the Global Quality Scale (two studies).
gain_evidence: pooled Global Quality Scale (GQS) score of 3.69 (95% CI: 3.58–3.80) | AI-supported cephalometric analysis significantly improved students’ landmarking accuracy before and after training
problem_reading: A systematic review of seven orthodontic education studies found 87.8% of North American programs lacked formal AI seminars and faculty cited high costs (89.3%) and lack of technical knowledge (94.7%).
problem_evidence: 87.8% lacked formal AI seminars | high costs (89.3%) and lack of technical knowledge (94.7%) | barriers such as limited curricular integration, lack of training, and faculty skepticism were recurrent
quick_read: A systematic review and meta-analysis of seven studies covering 1,101 participants examined how AI is used to teach orthodontics. The participants included 449 orthodontic students, 408 orthodontists, 149 faculty members, 41 program directors and 30 general dentists, plus 24 trainees in one quasi-experimental study. Tools ranged from cephalometric landmarking platforms to ChatGPT-based learning modules.

Only two studies had comparable data for pooling. They gave a Global Quality Scale score of 3.69 (95% CI 3.58–3.80) for ChatGPT-generated orthodontic content, described as moderate perceived quality, with heterogeneity of 64.5%. All other outcomes were summarised narratively because of inconsistent measures and missing statistics.

The findings point to learner benefit alongside slow institutional uptake. Students and junior faculty were more enthusiastic, while experienced orthodontists were more skeptical of AI content. Most programs lack the training, expertise and curricular space to teach it, and the evidence base is small and mostly non-randomized.
limitation: Only two studies could be pooled and I2 was 64.5%; the other outcomes relied on narrative synthesis of mostly small, non-randomized studies and self-reported survey data, which limits generalizability.
tag: Dual reading
key_points: Seven studies were included from 896 screened records and 107 full-text reviews; sample sizes ranged from 24 to 298 participants. | Two studies were pooled: ChatGPT-generated orthodontic content scored 3.69 on the Global Quality Scale (95% CI 3.58–3.80, I2 = 64.5%). | Lin et al. found AI-assisted digital cephalometry improved students' landmarking accuracy, with three rounds of training raising accuracy over time. | In a North American survey, 56.1% of residency programs had adopted or planned AI instruction, mostly for research (60.9%) rather than diagnosis (39.1%); 87.8% lacked formal AI seminars. | Orthodontists were more skeptical of chatbot answers (mean GQS 2.87–3.23) than students and general dentists (3.93–4.10). | Among faculty in one survey, 72% supported AI in postgraduate curricula, but 89.3% cited cost and 94.7% cited lack of technical knowledge as obstacles. | Risk of bias was low in three studies, moderate in three and serious in one; GRADE rated four studies moderate quality and three low.
rundown: The review followed PRISMA 2020 and was registered in PROSPERO. Searches of PubMed, Scopus, Web of Science and Embase ran through May 2025, and two reviewers screened and extracted data independently. Risk of bias was assessed with ROBINS-I and certainty with GRADE.

On skills, Lin et al. reported that AI-supported cephalometric training improved student landmarking accuracy through real-time visual feedback. Metin et al. found chatbot-assisted clinical reasoning scored comparably to human-guided sessions in accuracy and satisfaction, though ChatGPT-4 was less consistent than human responses.

Perceptions split by experience. In Kurt et al., patients rated ChatGPT highest (mean GQS 4.27 for clear aligners, 4.40 for lingual orthodontics) while orthodontists gave 3.43–3.67. In Gupta et al., 74% of faculty agreed AI improved cephalometric accuracy, yet 52% in another survey worried about AI errors in treatment planning.

Adoption lagged belief. Mengi et al. found 62.5% of clinicians did not use AI for cephalometric analysis because of cost and technical barriers, and more than 60% were not using AI in routine practice, even though 84% of respondents agreed it could improve diagnostic quality.
sources:
- peer_reviewed | Journal of Clinical Medicine | https://doi.org/10.3390/jcm14155487 | 2025-08-04
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