## 5 Results and Findings
### Machine Learning Approaches
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**No.** & **Ref., Year** & **Application** & **Model** & **Images Type** & **Performance Metric** \\ \hline \multirow{4}{*}{1} & \multirow{4}{*}{[52], 2022} & Recognizing and & & & \\  & classifying children’s & & & & \\ molars based on deep & & & & & \\ learning from dental & & & & & \\ photos. & & & & & \\ \hline \multirow{4}{*}{2} & \multirow{4}{*}{[53], 2021} & \multirow{4}{*}{[202]} & Modified extreme & & & \\ learning machine & & & & & \\ learning machine & & (MELM), sparse & & & \\ representation & & & & & \\ classification (SRC). & & & & & \\ \hline \multirow{4}{*}{3} & \multirow{4}{*}{[54], 2020} & Reconstructing & & & & \\ high-resolution (HR) & & & & & \\ dental X-ray images from & & (granular level feature extraction and & & & \\ low-resolution (LR) & & & & & \\ images for forensic & & polynomial regression & & & \\ \cline{1-1}  & & odontology. & & & \\ \hline \multirow{4}{*}{4} & \multirow{4}{*}{[55], 2023} & Automatic segmentation & Machine learning & & & \\ of trabecular bone in & & (decision tree, naive & & & \\ periapical radiographs for & & Bayes, multilayer & & radiographs. & Structural similarity index \\ osteoporosis detection. & & perceptron). & & & \\  & & & & & \\  & & & & & \\  & & & & & \\  & & & & & \\ \hline \multirow{4}{*}{5} & \multirow{4}{*}{[56], 2021} & Sex estimation in the & Geometric & & & \\ Indian population using & & morphometric analysis & (GMA) and artificial & & \\  & & neural network (ANN). & & & \\  & & & & & \\  & & & & & \\ \hline \multirow{4}{*}{6} & \multirow{4}{*}{[57], 2019} & Comparative analysis of & K-nearest neighbors & & & KNN algorithm in RGB \\ color-matching systems & & (KNN), neural network & & & & characteristic achieved \\ for teeth recognition. & & (NN), decision tree (DT). & & & & \\ \hline \multirow{2}{*}{7} & \multirow{2}{*}{[58], 2018} & \multirow{2}{*}{Caries detection.} & Intelligent level set. & Dental X-ray. & Accuracy = 98\%. \\ \cline{1-1}  & & & & & \\ \hline \multirow{2}{*}{8} & \multirow{2}{*}{[59], 2019} & \multirow{2}{*}{Artifact correction.} & Wasserstein generative & & & Improved artifact \\ adversarial networks. & & & & & \\ \hline \multirow{2}{*}{9} & \multirow{2}{*}{[60], 2020} & \multirow{2}{*}{Caries diagnosis.} & Backpropagation neural & & & \\ network. & & & & & \\ \hline \multirow{2}{*}{10} & \multirow{2}{*}{[61], 2020} & Human identification. & Learnable connected & & & \\ attention network. & & & & & \\ \hline \multirow{2}{*}{11} & \multirow{2}{*}{[62], 2022} & \multirow{2}{*}{Cavities localization.} & Hybrid Mask RCNN. & Mixed dental & & \\ photographic & & & & & \\ images. & & & & & \\ \hline \multirow{2}{*}{12} & \multirow{2}{*}{[63], 2023} & Diagnosis and treatment & Artificial intelligence & & & \\ planning. & & algorithm. & & & \\ \hline \multirow{2}{*}{13} & \multirow{2}{*}{[63], 64], 2023} & \multirow{2}{*}{Age estimation.} & Hybrid HCNN-KNN & Orthopantomography & & \\ model. & & & (OPG). & & \\ \hline \multirow{2}{*}{14} & \multirow{2}{*}{[65], 2022} & Detecting and classifying & & & & \\ occlusal caries on dental & & Mask R-CNN. & & Intraoral dental & \\ images. & & & & & \\ \hline \multirow{2}{*}{15} & \multirow{2}{*}{[66], 2022} & Detecting 17 fine-grained & & & & \\  & dental anomalies. & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Summary of the selected studies that use deep learning approaches.