Deep Learning and Machine Learning Techniques in Dental Disease Detection and Classification

Recent deep learning (DL) and machine learning (ML) developments have notably improved dental disease detection and classification automation. These methods utilise a combination of CNNS, transfer learning, and ensemble models to interpret radiographic images, intra-oral scans, and clinical information with impressive accuracy. The application of DL and ML technologies enhances the effectiveness of diagnosis, minimises human error, and aids in diagnosing disorders, including caries, periodontal disease, and oral cancer. This paper investigates recent available methodologies with their associated performance metrics and issues in industrial applications. Regarding research, translation, and clinical deployment, some future directions are also introduced, such as multimodal data fusion and explainable AI.