With increasing digitalization in orthodontics, certain orthodontic manufacturing processes such as the fabrication of indirect bonding trays, aligner production, or wire bending can be automated. However, orthodontic treatment planning and evaluatio...
The present study tested the combination of mandibular and dental dimensions for sex determination using machine learning. Lateral cephalograms and dental casts were used to obtain mandibular and mesio-distal permanent teeth dimensions, respectively....
The purpose of this study was to construct deep learning models for more efficient and reliable sex estimation. Two deep learning models, VGG16 and DenseNet-121, were used in this retrospective study. In total, 600 lateral cephalograms were analyzed....
Oral surgery, oral medicine, oral pathology and oral radiology
Feb 20, 2024
OBJECTIVES: Age and sex characteristics are evident in cephalometric radiographs (CRs), yet their accurate estimation remains challenging due to the complexity of these images. This study aimed to harness deep learning to automate age and sex estimat...
Oral surgery, oral medicine, oral pathology and oral radiology
Feb 12, 2024
OBJECTIVE: We examined the effectiveness and feasibility of the Mask Region-based Convolutional Neural Network (Mask R-CNN) for automatic detection of cephalometric landmarks on lateral cephalometric radiographs (LCRs).
OBJECTIVE: To investigate the accuracy of artificial intelligence-assisted growth prediction using a convolutional neural network (CNN) algorithm and longitudinal lateral cephalograms (Lat-cephs).
Journal of stomatology, oral and maxillofacial surgery
Jan 30, 2024
OBJECTIVE: To present a systematic review of the state of the art regarding clinical applications, main features, and outcomes of artificial intelligence (AI) in orthognathic surgery.
Oral surgery, oral medicine, oral pathology and oral radiology
Jan 22, 2024
OBJECTIVE: To assess the accuracy and reproducibility of cephalometric landmark identification performed by 2 artificial intelligence (AI)-driven applications (CefBot and WebCeph) and human examiners.
The journal of evidence-based dental practice
Dec 21, 2023
ARTICLE TITLE AND BIBLIOGRAPHIC INFORMATION: Artificial Intelligence for Detecting Cephalometric Landmarks: A Systematic Review and Meta-analysis. J Digit Imaging. 2023 Jun;36(3):1158-1179. doi:10.1007/s10278-022-00766-w.
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