Obrubov A A, Solovykh E A, Nadtochiy A G
Central Research Institute of Dentistry and Maxillofacial Surgery, Ministry of Health of the Russian Federation, Moscow, Russia.
Laboratory of Functional Diagnostics LLC, Moscow, Russia.
Bull Exp Biol Med. 2025 Apr;178(6):798-802. doi: 10.1007/s10517-025-06420-z. Epub 2025 May 30.
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.
我们展示了基于两个神经网络开发的Dentomo人工智能模型的结果。该模型包括一个数据库和一个与SNOMED CT协调一致的知识库，可用于处理和解释牙科系统的锥形束计算机断层扫描（CBCT）结果，特别是识别和分类牙齿、识别病理和既往治疗的CT征象。基于这些数据，人工智能可以得出结论并生成医学报告，对数据进行系统化整理，并从结果中学习。对Dentomo的诊断有效性进行了评估。该研究的初步结果表明，基于神经网络和人工智能的模型是临床实践中分析CBCT扫描以及优化牙医工作流程的宝贵工具。
