Applications and performance of artificial intelligence models in removable prosthodontics: A literature review.

Autor:	Ali IE; Department of Advanced Prosthodontics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.; Department of Prosthodontics, Faculty of Dentistry, Mansoura University, Mansoura, Egypt., Tanikawa C; Department of Orthodontics and Dentofacial Orthopedics, Graduate School of Dentistry, Osaka University, Suita, Japan., Chikai M; Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Japan., Ino S; Department of Mechanical Engineering, Graduate School of Engineering, Osaka University, Suita, Japan., Sumita Y; Department of Partial and Complete Denture, School of Life Dentistry at Tokyo, The Nippon Dental University, Tokyo, Japan.; Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan., Wakabayashi N; Department of Advanced Prosthodontics, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.
Jazyk:	angličtina
Zdroj:	Journal of prosthodontic research [J Prosthodont Res] 2024 Jul 08; Vol. 68 (3), pp. 358-367. Date of Electronic Publication: 2023 Oct 05.
DOI:	10.2186/jpr.JPR_D_23_00073
Abstrakt:	Purpose: In this narrative review, we present the current applications and performances of artificial intelligence (AI) models in different phases of the removable prosthodontic workflow and related research topics. Study Selection: A literature search was conducted using PubMed, Scopus, Web of Science, and Google Scholar databases between January 2010 and January 2023. Search terms related to AI were combined with terms related to removable prosthodontics. Articles reporting the structure and performance of the developed AI model were selected for this literature review. Results: A total of 15 articles were relevant to the application of AI in removable prosthodontics, including maxillofacial prosthetics. These applications included the design of removable partial dentures, classification of partially edentulous arches, functional evaluation and outcome prediction in complete denture treatment, early prosthetic management of patients with cleft lip and palate, coloration of maxillofacial prostheses, and prediction of the material properties of denture teeth. Various AI models with reliable prediction accuracy have been developed using supervised learning. Conclusions: The current applications of AI in removable prosthodontics exhibit significant potential for improving the prosthodontic workflow, with high accuracy levels reported in most of the reviewed studies. However, the focus has been predominantly on the diagnostic phase, with few studies addressing treatment planning and implementation. Because the number of AI-related studies in removable prosthodontics is limited, more models targeting different prosthodontic disciplines are required.
Databáze:	MEDLINE
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