The incidence of oral diseases, mainly dental caries and periodontal diseases, is increasing all over the world, including Norway, which results in serious health and economic consequences, and reduces the quality of life for those affected. It is estimated that half of the world's population suffers from tooth decay, the most common condition. Another widespread oral disease, severe periodontal (gum) disease, which can lead to tooth loss, is also increasing globally. In addition, dental treatment is usually expensive, averaging 5% of the total health costs and 20% of the health costs for the individual in high-income countries. It is a global public health problem to identify individuals and treat abnormal changes at an early stage, before any symptoms become noticeable. This will significantly contribute to reducing the overall health costs. Every year, around 75-85% of Norwegian adults over the age of 18 visit their dentists for an annual oral health check. To improve these controls, in the AI-Dentify project we want to develop, test and implement an automated computer-aided diagnostic tool to detect abnormalities as early as possible. In addition, it is of great interest to reduce variation in the interpretation of dental health images used in dental diagnostics between dentists, and also to be able to objectively grade and document findings effectively. Analysis of the X-rays taken during dental health check-ups with artificial intelligence technology has the potential to revolutionize dental health services and can help detect and characterize harmful changes early on in a robust / objective way.
The main ambition of the AI-Dentify project is to develop, test and validate a novel Boneprox software as a service platform, which is scalable to the global market. The solution will make it easy for the dental industry worldwide to use this as a complete solution on an everyday basis for decision support in oral disease diagnostics. The prevalence of non-communicable diseases particularly oral diseases are increasing worldwide including Norway. In Norway, every year more than 75% of adults visit their dentists for annual oral health check-up. We need to develop and integrate new research based computational models with the ability to automatically analyze data to retrieve useful information to aid clinicians in accurate diagnostics and decision making. Hence, we think modern-day supervised machine learning technique(s) may offer the promise to potentially solve this important issue. In dental science, a panoramic dental X-ray image (Orthopantomogram, known as OPG) captures both maxillary and mandibular dental arches and the surrounding structures including hypoid bone. We believe that implementing artificial intelligence based algorithms can reduce the rate of diagnosing false negatives, especially effective for inexperienced dentists for decision making. Thus, the overall goal of this project is to develop deep learning classification model based on computer-assisted diagnosis system using dental X-ray images to detect oral abnormalities such as caries and periodontitis, and used as a decision making tool.