Deep learning-based approach for differential diagnosis of odontogenic cysts from histopathological images

It was observed that VGG16 and VGG19 models showed superior performance on the data set in question, while Xception and Inception V3 models converged slower, meaning the training process progressed slower. Results showed that deep neural networks can be efficiently used in detecting OCs. AI-based OC detection may be a decision support tool that reduces interprofessional variability, expedites the diagnostic process, and lessens clinician workload.