AIMC Topic: Molar

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Application of 3D neural networks and explainable AI to classify ICDAS detection system on mandibular molars.

The Journal of prosthetic dentistry
STATEMENT OF PROBLEM: Considerable variations exist in cavity preparation methods and approaches. Whether the extent and depth of cavity preparation because of the extent of caries affects the overall accuracy of training deep learning models remains...

External validation of an artificial intelligence-based method for the detection and classification of molar incisor hypomineralisation in dental photographs.

Journal of dentistry
OBJECTIVES: This ex vivo diagnostic study aimed to externally validate an open-access artificial intelligence (AI)-based model for the detection, classification, localisation and segmentation of enamel/molar incisor hypomineralisation (EH/MIH).

Novel AI-based automated virtual implant placement: Artificial versus human intelligence.

Journal of dentistry
OBJECTIVES: To assess quality, clinical acceptance, time-efficiency, and consistency of a novel artificial intelligence (AI)-driven tool for automated presurgical implant planning for single tooth replacement, compared to a human intelligence (HI)-ba...

Identification of Root Canal Morphology in Fused-rooted Mandibular Second Molars From X-ray Images Based on Deep Learning.

Journal of endodontics
INTRODUCTION: Understanding the intricate anatomical morphology of fused-rooted mandibular second molars (MSMs) is essential for root canal treatment. The present study utilized a deep learning approach to identify the three-dimensional root canal mo...

Panoramic Radiography in the Evaluation of the Relationship of Maxillary Molar Teeth and Maxillary Sinuses on the Deep Learning Models Improved with the Findings Obtained by Cone Beam Computed Tomography.

Nigerian journal of clinical practice
BACKGROUND: Panoramic radiography (PR) is available to determine the contact relationship between maxillary molar teeth (MMT) and the maxillary sinus floor (MSF). However, as PRs do not provide clear and detailed anatomical information, advanced imag...

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

International journal of paediatric dentistry
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.

Fully automated deep learning approach to dental development assessment in panoramic radiographs.

BMC oral health
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 ...

A retrospective longitudinal assessment of artificial intelligence-assisted radiographic prediction of lower third molar eruption.

Scientific reports
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...

Is ChatGPT a reliable source of scientific information regarding third-molar surgery?

Journal of the American Dental Association (1939)
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...

Automatic diagnosis of true proximity between the mandibular canal and the third molar on panoramic radiographs using deep learning.

Scientific reports
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...