INTRODUCTION: Supernumerary teeth are a common developmental anomaly in pediatric patients, potentially leading to complications such as impaction, crowding, and delayed eruption. Accurate and early detection is critical to prevent these sequelae and...
BACKGROUND: With the growing capabilities of language models like ChatGPT to process text and images, this study evaluated their accuracy in detecting supernumerary teeth on periapical radiographs. A customized GPT-4V model (CGPT-4V) was also develop...
Journal of stomatology, oral and maxillofacial surgery
Feb 19, 2025
OBJECTIVES: The aim of this study was to compare the effectiveness of automated supernumerary tooth (ST) detection systems on periapical radiographs using Faster R-CNN and YOLOv8 with detection by 8 dental residents.
OBJECTIVES: This study aimed to develop and validate a robotic system capable of performing accurate and minimally invasive jawbone milling procedures in oral and maxillofacial surgery.
The aim of this study was to develop an optimal, simple, and lightweight deep learning convolutional neural network (CNN) model to detect the presence of mesiodens on panoramic radiographs. A total of 628 panoramic radiographs with and without mesiod...
The aim of the feasibility study was to construct deep learning models for the classification of multiple dental anomalies in panoramic radiographs. Panoramic radiographs with single supernumerary teeth and/or odontomas were considered the "case" gro...
International journal of paediatric dentistry
Mar 30, 2022
BACKGROUND: Supernumerary teeth are a common anomaly and are frequently observed in paediatric patients. To prevent or minimize complications, early diagnosis and treatment is ideal in children with supernumerary teeth.
Oral surgery, oral medicine, oral pathology and oral radiology
Jun 2, 2020
OBJECTIVE: This investigation aimed to verify and compare the performance of 3 deep learning systems for classifying maxillary impacted supernumerary teeth (ISTs) in patients with fully erupted incisors.
To systematically evaluate artificial intelligence applications for diagnostic and treatment planning possibilities in pediatric dentistry. PubMed, EMBASE, Scopus, Web of Science, IEEE, medRxiv, arXiv, and Google Scholar were searched using specifi...
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