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Published on: February 23, 2024
Application of Artificial Intelligence Models in Oral and Maxillofacial Prosthesis Restoration: A Systematic Review
Rui Luo1, Tengteng Zhang1, Guo Lin1
1Xinjiang Medical University Stomatological College, Urumqi, China.
Background:
Artificial intelligence (AI) is increasingly favoured in the medical field, and the traditional maxillofacial prosthetic system has complex processes, low efficiency, and relatively insufficient model matching and aesthetic outcomes. With the rapid development of AI, it is expected that AI technology will address the shortcomings of these traditional methods.
Purpose:
To comprehensively analyse the research on AI in maxillofacial prosthetic image acquisition, data analysis, and colouring, and to elaborate on its application evaluation and future trends to improve the diagnosis and treatment experience of patients.
Material And Methods:
Based on the PICO principle, we searched the PubMed, Web of Science, and Cochrane databases, as well as conducted manual searches, and screened English articles from January 2016 to January 2024 according to specific inclusion and exclusion criteria. Quality assessment was performed by 2 investigators using the JBI Quasi-Experimental Study Critical Assessment Checklist.
Results:
A total of 17 related articles were identified, including 7 in the field of image acquisition, 8 in the field of data analysis, and 2 in the field of pseudo colouring. The results show that the application of AI in these 3 fields is on the rise, reaching a record high in 2024.
Conclusions And Clinical Relevance:
There is a lack of literature available for analysis, all studies have demonstrated high accuracy and clinical necessity. However, there is a relative lack of consideration when it comes to the comfort and efficiency of patients and doctors in practice, which is a key direction for future AI software development. In addition, we need more research on irregular bone or personalized model design, as well as more accurate analysis of complex structures that are vulnerable to damage.

