Artificial Intelligence Application in a Case of Mandibular Third Molar Impaction: A Systematic Review of the Literature

被引:4
作者
Assiri, Hassan Ahmed [1 ]
Hameed, Mohammad Shahul [1 ]
Alqarni, Abdullah [1 ]
Dawasaz, Ali Azhar [1 ]
Arem, Saeed Abdullah [1 ]
Assiri, Khalil Ibrahim [1 ]
机构
[1] King Khalid Univ, Coll Dent, Dept Diag Sci & Oral Biol, POB 960, Abha 61421, Saudi Arabia
基金
英国科研创新办公室;
关键词
impacted tooth; mandibular third molar; artificial intelligence; panoramic radiography; cone beam computed tomography;
D O I
10.3390/jcm13154431
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Objective: This systematic review aims to summarize the evidence on the use and applicability of AI in impacted mandibular third molars. Methods: Searches were performed in the following databases: PubMed, Scopus, and Google Scholar. The study protocol is registered at the International Platform of Registered Systematic Review and Meta-analysis Protocols (INPLASY202460081). The retrieved articles were subjected to an exhaustive review based on the inclusion and exclusion criteria for the study. Articles on the use of AI for diagnosis, treatment, and treatment planning in patients with impacted mandibular third molars were included. Results: Twenty-one articles were selected and evaluated using the Scottish Intercollegiate Guidelines Network (SIGN) evidence quality scale. Most of the analyzed studies dealt with using AI to determine the relationship between the mandibular canal and the impacted mandibular third molar. The average quality of the articles included in this review was 2+, which indicated that the level of evidence, according to the SIGN protocol, was B. Conclusions: Compared to human observers, AI models have demonstrated decent performance in determining the morphology, anatomy, and relationship of the impaction with the inferior alveolar nerve canal. However, the prediction of eruptions and future horizons of AI models are still in the early developmental stages. Additional studies estimating the eruption in mixed and permanent dentition are warranted to establish a comprehensive model for identifying, diagnosing, and predicting third molar eruptions and determining the treatment outcomes in the case of impacted teeth. This will help clinicians make better decisions and achieve better treatment outcomes.
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页数:13
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