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This study developed a machine-learning algorithm for the automatic detection and classification of dental restorations in panoramic radiographs, achieving a detection rate of 94.6% and classification accuracy of 93.6%. The algorithm utilized a combination of image processing techniques and a Cubic Support Vector Machine for classification, analyzing 738 restorations across 83 images. The findings suggest that this AI approach could enhance diagnostic accuracy and facilitate better patient management in den

Author

belo.patrick

Language

EN