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Artificial intelligence models for tooth-supported fixed and removable prosthodontics: A systematic review.
Marta Revilla-León1, Miguel Gómez-Polo2, Shantanu Vyas3
1Affiliate Assistant Professor, Graduate Prosthodontics, Department of Restorative Dentistry, School of Dentistry, University of Washington, Seattle, Wash and Faculty and Director of Research and Digital Dentistry, Kois Center, Seattle, Wash; Adjunct Professor, Department of Prosthodontics, School of Dental Medicine, Tufts University, Boston, MA.
Artificial intelligence (AI) shows promise in prosthodontics for tasks like shade selection and restoration design. Further research is needed to fully assess AI
Area of Science:
- Dentistry
- Prosthodontics
- Artificial Intelligence
Background:
- The application of artificial intelligence (AI) in prosthodontics is growing.
- A systematic analysis of AI's current development and performance in prosthodontics is lacking.
Approach:
- A systematic review of electronic databases (MEDLINE/PubMed, EMBASE, Web of Science, Cochrane, Scopus) and manual searches was conducted.
- Studies were selected based on AI applications in tooth shade selection, automated restoration design, margin line mapping, casting optimization, facial change prediction, and removable partial denture design.
- Study quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Quasi-Experimental Studies.
Key Points:
- AI models demonstrated improved tooth shade matching compared to visual selection.
- Automated dental restoration design showed feasibility in 14 studies.
- AI accurately mapped preparation finishing lines (90.6%-97.4%) and optimized casting processes, reducing defects and manufacturing time.
- AI models were developed for predicting facial changes and designing removable partial dentures.
Conclusions:
- AI holds potential as a reliable diagnostic tool in various prosthodontic applications.
- Current AI models in prosthodontics are still under development.
- Further studies are essential to advance and evaluate the clinical performance of AI in prosthodontics.
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