AI Medical Compendium Journal:
Dento maxillo facial radiology

Showing 71 to 74 of 74 articles

Machine learning assessment of dental age classification based on cone-beam CT images: a different approach.

Dento maxillo facial radiology
OBJECTIVES: Machine learning (ML) algorithms are a portion of artificial intelligence that may be used to create more accurate algorithmic procedures for estimating an individual's dental age or defining an age classification. This study aims to use ...

Comparison of deep learning methods for the radiographic detection of patients with different periodontitis stages.

Dento maxillo facial radiology
OBJECTIVES: The objective of this study is to assess the accuracy of computer-assisted periodontal classification bone loss staging using deep learning (DL) methods on panoramic radiographs and to compare the performance of various models and layers.

Deep learning for tooth identification and numbering on dental radiography: a systematic review and meta-analysis.

Dento maxillo facial radiology
OBJECTIVES: Improved tools based on deep learning can be used to accurately number and identify teeth. This study aims to review the use of deep learning in tooth numbering and identification.

Detection of vertical root fractures by cone-beam computed tomography based on deep learning.

Dento maxillo facial radiology
OBJECTIVES: This study aims to evaluate the performance of ResNet models in the detection of and vertical root fractures (VRF) in Cone-beam Computed Tomography (CBCT) images.