AI-Driven Dental Anomaly Detection System

Our startup, dedicated to innovating within the dental care industry, is looking to develop an AI-driven system that utilizes advanced machine learning techniques to identify dental anomalies from X-ray images. This project will leverage computer vision models, such as YOLO and TensorFlow, to detect and classify common dental issues like cavities, misalignments, and periodontal disease with a high degree of accuracy. The system should integrate with existing dental software to provide seamless, real-time analysis, aiding dentists in making informed decisions quickly. The project will involve developing and training machine learning models using a dataset of dental X-rays, implementing an intuitive interface for easy dentist interaction, and ensuring that the system can operate efficiently on both cloud and edge devices for maximum accessibility. We are looking to achieve a significant reduction in diagnostic errors and increase the efficiency of dental check-ups. Key deliverables include a fully functional prototype, documentation, and training materials for dental professionals. The successful candidate will have experience with AI frameworks, data preprocessing, and deployment of AI models in real-world applications.