AIMC Topic: Molar

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Deep learning-based detection of irreversible pulpitis in primary molars.

International journal of paediatric dentistry May 9, 2024
BACKGROUND: Changes in healthy and inflamed pulp on periapical radiographs are traditionally so subtle that they may be imperceptible to human experts, limiting its potential use as an adjunct clinical diagnostic feature.
Male Deep Learning Child, Preschool Female Sensitivity and Specificity Tooth, Deciduous Molar Pulpitis Child Feasibility Studies Humans Retrospective Studies
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Fully automated deep learning approach to dental development assessment in panoramic radiographs.

BMC oral health Apr 6, 2024
BACKGROUND: Dental development assessment is an important factor in dental age estimation and dental maturity evaluation. This study aimed to develop and evaluate the performance of an automated dental development staging system based on Demirjian's ...
Age Determination by Teeth Molar Deep Learning Incisor Humans Child Radiography, Panoramic
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A retrospective longitudinal assessment of artificial intelligence-assisted radiographic prediction of lower third molar eruption.

Scientific reports Jan 10, 2024
Prediction of lower third molar eruption is crucial for its timely extraction. Therefore, the primary aim of this study was to investigate the prediction of lower third molar eruption and its uprighting with the assistance of an artificial intelligen...
Humans Infant Molar, Third Molar Artificial Intelligence Retrospective Studies Tooth Eruption
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Is ChatGPT a reliable source of scientific information regarding third-molar surgery?

Journal of the American Dental Association (1939) Jan 8, 2024
BACKGROUND: ChatGPT (OpenAI) is a large language model. This model uses artificial intelligence and machine learning techniques to generate humanlike language and responses, even to complex questions. The authors aimed to assess the reliability of re...
Molar, Third Molar Health Personnel Reproducibility of Results Humans Artificial Intelligence
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Automatic diagnosis of true proximity between the mandibular canal and the third molar on panoramic radiographs using deep learning.

Scientific reports Dec 12, 2023
Evaluating the mandibular canal proximity is crucial for planning mandibular third molar extractions. Panoramic radiography is commonly used for radiological examinations before third molar extraction but has limitations in assessing the true contact...
Mandible Radiography, Panoramic Molar Cone-Beam Computed Tomography Mandibular Canal Deep Learning
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Semi-supervised automatic dental age and sex estimation using a hybrid transformer model.

International journal of legal medicine Jan 31, 2023
Teeth-based age and sex estimation is an important task in mass disasters, criminal scenes, and archeology. Although various methods have been proposed, most of them are subjective and influenced by observers' experiences. In this study, we aimed to ...
Molar Tooth Crown Bicuspid Adolescent Child, Preschool Male Dental Pulp Cavity Neural Networks, Computer Humans Female Adult
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Variational autoencoder-based estimation of chronological age and changes in morphological features of teeth.

Scientific reports Jan 13, 2023
This study led to the development of a variational autoencoder (VAE) for estimating the chronological age of subjects using feature values extracted from their teeth. Further, it determined how given teeth images affected the estimation accuracy. The...
Artificial Intelligence Age Determination by Teeth Molar Cuspid
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Accuracy of artificial intelligence-designed single-molar dental prostheses: A feasibility study.

The Journal of prosthetic dentistry Jan 9, 2023
STATEMENT OF PROBLEM: Computer-aided design and computer-aided manufacturing (CAD-CAM) technology has greatly improved the efficiency of the fabrication of dental prostheses. However, the design process (CAD stage) is still time-consuming and labor i...
Models, Dental Computer-Aided Design Feasibility Studies Molar Dental Prosthesis Humans Artificial Intelligence Adult Dental Prosthesis Design
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Development and international validation of logistic regression and machine-learning models for the prediction of 10-year molar loss.

Journal of clinical periodontology Dec 11, 2022
AIM: To develop and validate models based on logistic regression and artificial intelligence for prognostic prediction of molar survival in periodontally affected patients.
Periodontitis Bayes Theorem Machine Learning Tooth Loss Molar Neural Networks, Computer Humans Logistic Models Artificial Intelligence
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Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography.

Scientific reports Oct 8, 2022
In this study, the accuracy of the positional relationship of the contact between the inferior alveolar canal and mandibular third molar was evaluated using deep learning. In contact analysis, we investigated the diagnostic performance of the presenc...
Mandibular Nerve Mandible Deep Learning Molar Radiography, Panoramic Molar, Third
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