Introduction: Artificial intelligence (AI) models are now an integral part of clinical dental practice. In restorative dentistry, AI has been used to improve dental caries diagnosis through periapical and bitewing radiographs, predict the failure of a dental restoration, and diagnose vertical tooth fracture by using periapical radiographs or CBCT data.
AI models have been applied to mapping the finishing line of tooth preparations or assisting in tooth anatomy selection for the automated design of dental restorations by using CAD methods. The aim of this systematic review was to evaluate the performance of AI models in the prosthodontic field.
Material and methods: An electronic systematic review was performed in MEDLINE/PubMed, EMBASE, Web of Science, Cochrane, and Scopus. A manual search was also conducted after referencing revision. Studies with AI models were selected based on six criteria: tooth shade selection, automated fabrication of dental restorations, replication of the finishing line of tooth preparations, optimization of the manufacturing casting process, prediction of facial changes in patients with removable prostheses and removable design of partial dentures.
Results. A total of 36 articles were reviewed and classified into six groups based on the application of the AI model. One article reported on the development of an AI model for tooth shade selection, reporting better shade matching than with conventional visual selection. Fourteen articles reported on the feasibility of automated design of dental restorations using different AI models.
An AI model was able to mark the margin line without manual interaction with an average accuracy ranging from 90.6% to 97.4%. Two investigations developed AI algorithms for optimizing the manufacturing casting process, reporting an improvement of the design process, minimizing the porosity on the cast metal and reducing the overall manufacturing time.
One study proposed an AI model that was able to predict facial changes in patients using removable prostheses. Seventeen investigations were included that focused on developing clinical decision support, expert systems for designing removable partial dentures for clinicians and educational purposes, computer-aided learning with video interactive programs for student learning, and automated removable partial denture design.
Conclusions. AI models have shown the potential for providing a reliable diagnostic tool for tooth shade selection, automated restoration design, mapping the preparation finishing line, optimizing the manufacturing casting, predicting facial changes in patients with removable prostheses, and designing removable partial dentures, but they are still in development. The authors said additional studies are needed to further develop and assess their clinical performance.
Revilla-León M, Gómez-Polo M, Vyas S, Barmak AB, Gallucci GO, Att W, Özcan M, Krishnamurthy VR. "Artificial intelligence models for tooth-supported fixed and removable prosthodontics: A systematic review." J Prosthet Dent. 2023 Feb;129(2):276-292. doi: 10.1016/j.prosdent.2021.06.001. Epub 2021 Jul 17. PMID: 34281697.
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