AIMC Topic: Dentition, Permanent

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A novel deep learning-based model for automated tooth detection and numbering in mixed and permanent dentition in occlusal photographs.

BMC oral health Mar 29, 2025
BACKGROUND: While artificial intelligence-driven approaches have shown great promise in dental diagnosis and treatment planning, most research focuses on dental radiographs. Only three studies have explored automated tooth numbering in oral photograp...
Neural Networks, Computer Deep Learning Humans Dentition, Permanent Dentition, Mixed Tooth Photography, Dental
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Fully automated method for three-dimensional segmentation and fine classification of mixed dentition in cone-beam computed tomography using deep learning.

Journal of dentistry Oct 22, 2024
OBJECTIVE: To establish a high-precision, automated model using deep learning for the fine classification and three-dimensional (3D) segmentation of mixed dentition in cone-beam computed tomography (CBCT) images.
Humans Dentition, Mixed Cone-Beam Computed Tomography Imaging, Three-Dimensional Image Processing, Computer-Assisted Dentition, Permanent Deep Learning Child Female Male
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An explainable predictive model of direct pulp capping in carious mature permanent teeth.

Journal of dentistry Jul 31, 2024
OBJECTIVE: To introduce a novel approach for predicting the personalized probability of success of DPC treatment in carious mature permanent teeth using explainable machine learning (ML) models.
Middle Aged Treatment Outcome Adult Male Dental Pulp Capping Dental Caries Dentition, Permanent Humans Machine Learning Retrospective Studies Female
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Robust automated teeth identification from dental radiographs using deep learning.

Journal of dentistry Jul 6, 2023
OBJECTIVES: This study developed and validated a deep learning-based method to automatically segment and number teeth in panoramic radiographs across primary, mixed, and permanent dentitions.
Radiography, Panoramic Dentition, Permanent Algorithms Deep Learning
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Automated permanent tooth detection and numbering on panoramic radiograph using a deep learning approach.

Oral surgery, oral medicine, oral pathology and oral radiology Jun 8, 2023
OBJECTIVE: This study aimed to assess the performance of the deep learning (DL) model for automated tooth numbering in panoramic radiographs.
Humans Radiography, Panoramic Radiographic Image Interpretation, Computer-Assisted Tooth Dentition, Permanent Male Neural Networks, Computer Deep Learning Software
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Comparison of different machine learning approaches to predict dental age using Demirjian's staging approach.

International journal of legal medicine Jan 7, 2021
CONTEXT: Dental age, one of the indicators of biological age, is inferred by radiological methods. Two of the most commonly used methods are using Demirjian's radiographic stages of permanent teeth excluding the third molar (Demirjian's and Willems' ...
Molar, Third Female Child, Preschool Mandible Machine Learning Age Determination by Teeth Child Young Adult Algorithms Dentition, Permanent Male Humans Radiography, Panoramic Adolescent France
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Evaluation of the efficiency of computerized algorithms to formulate a decision support system for deepbite treatment planning.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Apr 1, 2021
INTRODUCTION: This study aimed to evaluate the efficiency of a newly constructed computer-based decision support system (DSS) on the basis of artificial intelligence technology and designed to plan treatment for patients with a deep overbite.
Cephalometry Malocclusion Dentition, Permanent Algorithms Mandible Humans Artificial Intelligence
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