AI tools to help dental students check and improve tooth preparations for metal-ceramic crowns
Official title: IntelliPrep: An AI-Driven Digital Self-Assessment Framework for Preclinical Tooth Preparation-A Randomized Controlled Trial
Run by Alexandria University · NCT07462156 · Data updated 2026-11-12
This project tests whether two AI-powered digital self-check tools help third-year dental students make more accurate tooth preparations and learn faster than traditional faculty feedback.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 18 Years to 20 Years |
| Sex | All |
| Enrollment | 36 (estimated) |
| Sponsor | Alexandria University Academic / other |
| Locations | 1 site (El Alamein) |
| Status | Recruiting |
| Started | February 1, 2026 |
| Main results expected | March 25, 2026 |
| Study ends | March 25, 2026 |
| Registry record updated | March 10, 2026 |
| Trial ID | NCT07462156 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal participants are third-year preclinical dental students who have completed the fixed prosthodontics tooth-preparation course and have no prior formal experience with digital 3D tooth-preparation assessment software.
✕Probably not a fit
Students who previously repeated the course, have substantial prior experience with digital metrology/3D inspection software, or cannot attend all scheduled training and examination sessions are unlikely to benefit.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
Third-year preclinical dental students who completed the fixed prosthodontics course will be assigned to one of three groups: traditional faculty feedback, a non-metrology-grade AI digital self-assessment tool, or a metrology-grade digital assessment tool. Over a defined training period they will produce tooth preparations for metal-ceramic crowns and use the assigned feedback method between practice sessions. Objective measures of preparation accuracy will be recorded by the digital systems and/or faculty scoring, and student learning outcomes will be tracked over time. Results from the three groups will be compared to see if the AI-assisted tools change preparation quality or learning trajectories.
Why it matters
Potential benefit: If successful, the tools could help students reach consistent, higher-quality tooth preparations sooner, which may translate into more reliable clinical care for future patients.
How similar studies have gone: Prior studies of digital or AI-assisted feedback in dental education have shown promising improvements in objective feedback and student performance, though results vary by tool and context.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Third-year preclinical dental student * Completion of the fixed prosthodontics tooth-preparation course. * No prior formal training or use of digital 3D tooth-preparation assessment software. Exclusion Criteria: * previous repetition of the course * Substantial prior experience with digital metrology/3D inspection software * Inability to attend all scheduled training and examination sessions.
Where it's running
-
College of Dentistry El Alamein - AAST
El Alamein, Egypt Recruiting
Study contacts
- Study coordinator: Mahinour Yousry, PhD
- Email: dr.mahinour.ahmed@aast.edu
- Phone: +2 01060080088
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.