[Artificial intelligence in predicting the risk of facial bone osteoporosis: clinical significance and prospects.].

Osteoporosis of the jawbones is a significant concern in dental practice, particularly for implant treatment planning. This review summarizes current diagnostic approaches with a focus on the use of artificial intelligence (AI) algorithms, including convolutional neural networks, for analyzing panoramic radiographs and cone-beam computed tomography. The findings demonstrate that AI models achieve high diagnostic accuracy in the automated classification of radiographic images, comparable to dual-energy X-ray absorptiometry. AI reduces subjectivity in image interpretation, although further standardization, dataset expansion, and development of explainable models are necessary. The review highlights comparative metrics of various neural network architectures and their potential for integration into clinical workflows.