# Investigation on the Application of Artificial Intelligence in Prostodontics
## 2 Methodology
### Study Characteristics
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Study Title, Author Name and** & **Country** & **Study Design** & **Journal** & **Aim of the Study** \\ \hline  & & & & This review covered eight orthodontic domains: (1) robotic dental assistants; (2) robotics in orthodontic diagnosis and simulation; (3) robotics in patient education, teaching, and training; (4) wire bending and customized appliance robotics; (5) nanorobots/microrobots for tooth movement acceleration and remote monitoring; (6) robotics in maxillofacial surgeries and implant placement; (7) automated aligner production robotics; and (8) TMD rehabilitation robotics. \\ \hline A review of 3D printing in & & & Three-dimensional printing has uses in dentistry; including prosthodntics, oral and maxillofacial surgery, and oral implantology. The 3D printing review is practical and scientific. \\ \hline Economic Evaluations of & & & For the purpose of providing a critical analysis of the techniques employed in comprehensive economic assessments of preventative therapies for dental caries and periodontitis. \\ \hline Rehabilitation with dental & & & The aim was to determine whether or not oral prosthesis rehabilitation was associated with an increase in regional brain activity. \\ \hline  & & & \\ Detection of Caries under Fixed & & & \\ Prosthodontic restorations Using & & & \\ Cone-beam CT: A Meta-analysis & & & \\ ([PERSON] et al. [51]) & & & \\ \hline Intraaoral scanning devices applied & & & \\ in fixed prosthodntics & Cuenca & Dentistry & Acta Sci Dent Sci & \\ ([PERSON] et al. [52]) & & & \\ \hline Efficacy of deep convolutional & & & & \\ neural network algorithm for the identification and classification of & & & \\ dental implant systems, using & & & \\ panoramic and periapical & & & \\ radiographs: A pilot study & & & \\ ([PERSON], 2020 [53]) & & & \\ \hline Artificial intelligence in fixed & & & \\ implant prosthodntics: A retrospective study of 106 & & & \\ implant-supported monolithic zirconia crowns inserted in the & & & \\ posterior jaws of 90 patients & & & \\ ([PERSON] et al., 2020 [54]) & & & \\ \hline Predicting the debonding of & & & \\ CAD/CAM composite & & & \\ resin crowns with AI & & & \\ ([PERSON] et al., 2019 [55]) & & & \\ \hline Detection and diagnosis of dental & & & \\ caries using a deep learning-based & & & \\ convolutional neural network & & & \\ algorithm ([PERSON] et al., 2018 [56]) & & & \\ \hline \hline \end{tabular}  
* The aim of the study was to estimate the efficacy of deep CNN algorithms for detection and diagnosis of dental caries on peripheral radiographs.
* The aim of the study was to assess the validity of deep learning with a CNN method to predict the debonding probability of CAD/CAM composite resins restorations from 2D images captured from 3D STL models of a die scanned by a 3D oral scanner.  
\end{table} 
Table 1: _Cont._Assessment of the Risk of Bias in Included Studies  
The papers that were included had their bias risk evaluated separately by the two researchers. The research was considered to have a low risk of bias if it provided thorough information on 80% or more of the relevant parameters. There was a moderate probability