Dental Disease Detection on Deep Learning Using Convolutional Neural Network

Dental diseases such as cavities, gingivitis, and periodontal infections are common oral health problems that require early diagnosis for effective treatment. This project proposes a deep learning-based dental disease detection system using dental X-ray images and computer vision techniques. The developed model utilizes Convolutional Neural Networks (CNN) and YOLOv8 algorithms to identify and classify various dental abnormalities with improved accuracy and speed. The dataset consists of annotated dental images used for training, validation, and testing of the model. The system aims to assist dentists by providing automated and real-time detection results, reducing manual effort and diagnostic errors. Experimental results demonstrate that the proposed approach achieves reliable performance for intelligent dental healthcare applications.

Keywords: Dental Disease Detection, Deep Learning, Convolutional Neural Networks (CNN), YOLOv8, Dental X-ray Analysis, Artificial Intelligence in Healthcare, Image Classification, Computer Vision, Oral Disease Prediction, Medical Image Processing.

Arunkumar, Lakshmi kalyan, Bharath (2026). Dental Disease Detection on Deep Learning Using Convolutional Neural Network. International Journal of Innovative Research in Multidisciplinary Education & Technology (IJIRMET), 11(3).