Development and evaluation of a deep learning-based system for dental age estimation using the demirjian method on panoramic radiographs

The AI-assisted system demonstrated comparable accuracy to the manual Demirjian method and showed higher performance in later stages of tooth development. The developed Python script and graphical interface allow for rapid, scalable, and user-friendly application of the method. While the system shows promise for use in clinical and forensic settings, broader validation with diverse populations and alternative model architectures is recommended before clinical deployment.