Diagnostic Efficiency of an Artificial Intelligence-Based Technology in Dental Radiography.
Authors
Affiliations (3)
Affiliations (3)
- Central Research Institute of Dentistry and Maxillofacial Surgery, Ministry of Health of the Russian Federation, Moscow, Russia. [email protected].
- Laboratory of Functional Diagnostics LLC, Moscow, Russia.
- Central Research Institute of Dentistry and Maxillofacial Surgery, Ministry of Health of the Russian Federation, Moscow, Russia.
Abstract
We present results of the development of Dentomo artificial intelligence model based on two neural networks. The model includes a database and a knowledge base harmonized with SNOMED CT that allows processing and interpreting the results of cone beam computed tomography (CBCT) scans of the dental system, in particular, identifying and classifying teeth, identifying CT signs of pathology and previous treatments. Based on these data, artificial intelligence can draw conclusions and generate medical reports, systematize the data, and learn from the results. The diagnostic effectiveness of Dentomo was evaluated. The first results of the study have demonstrated that the model based on neural networks and artificial intelligence is a valuable tool for analyzing CBCT scans in clinical practice and optimizing the dentist workflow.