Oral health diseases are a major healthcare concern, and many dental problems remain undetected due to manual examination of X-ray images, limited expert availability, and variation in diagnostic accuracy. This project, AI-Based Dental Intelligence System for Automated Detection and Diagnosis of Dental Diseases, aims to develop a web-based clinical decision support system that assists dentists in analyzing panoramic dental X-ray images. The system allows users to upload X-rays, automatically detect individual teeth, classify dental conditions, and generate structured diagnostic results with visual feedback. The proposed solution uses artificial intelligence and deep learning techniques to improve diagnostic speed, consistency, and reliability. Tooth localization is performed using an object detection model, while disease classification is supported through multiple deep learning models. A consensus-based decision approach is applied to combine model predictions and produce a more reliable final diagnosis. The system is designed with a user-friendly web interface for dentists and includes administrative features for user management, model updates, monitoring, and system configuration. By providing accurate AI-assisted diagnostic insights, this project aims to reduce human error, support early detection of dental diseases, and improve accessibility to intelligent dental healthcare solutions. The system is not intended to replace dentists but to serve as a dependable second op
Tools: Python,Jinja2,VsCode,Google Colab,Figma,CLIP,EfficientNet,ResNet
Department: Department of Computer Science
Poster
