CA24147 - Artificial Intelligence Driven Dental AgEstimation Network (AID-AgE)

Accurate estimation of biological age is essential in clinical and forensic fields, particularly in legal medicine, pediatrics, and orthodontics. Dental age estimation, involves several methods that rely on the analysis of teeth development, structure, and wear. Current dental age estimation techniques while effective, exhibit significant variability due to the lack of standardization and interindividual differences. This variability can result in inconsistent and sometimes unreliable outcomes, which may carry serious legal and clinical consequences.

The primary goal of this COST action is to develop artificial intelligence (AI)-driven models that enhance accuracy and reliability in dental age estimation, by analyzing dental radiographs (panoramic, periapical, and cone-beam CT).

The project aims to foster a collaborative research environment by bringing together experts in dentistry, AI, radiology, and forensic science. This will be achieved through working groups focused on data collection, AI model development, validation, and clinical integration.
AI models will be developed and trained to analyze dental development stages, such as tooth mineralization and root formation, with the aim of automating and improving the accuracy of traditional methods. The software tools developed will be user-friendly to ensure widespread adoption in medical and legal contexts and account for genetic, environmental, and socio-economic factors. The long-term goal is to establish global standards for dental age estimation techniques, with the potential for widespread adoption in both clinical and legal fields.
This project promises to revolutionize dental age estimation by integrating cutting-edge AI with traditional methods, enhancing precision, and facilitating more reliable and standardized practices worldwide.