AI Medical Compendium Topic

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Radiography, Panoramic

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Eichner classification based on panoramic X-ray images using deep learning: A pilot study.

Bio-medical materials and engineering
BACKGROUND: Research using panoramic X-ray images using deep learning has been progressing in recent years. There is a need to propose methods that can classify and predict from image information.

Diagnostic capability of artificial intelligence tools for detecting and classifying odontogenic cysts and tumors: a systematic review and meta-analysis.

Oral surgery, oral medicine, oral pathology and oral radiology
OBJECTIVE: To evaluate the diagnostic capability of artificial intelligence (AI) for detecting and classifying odontogenic cysts and tumors, with special emphasis on odontogenic keratocyst (OKC) and ameloblastoma.

Diagnostic accuracy of artificial intelligence versus manual detection in marginal bone loss around fixed prosthesis. a systematic review.

JPMA. The Journal of the Pakistan Medical Association
OBJECTIVES: The aim of the review is to evaluate the existing precision of artificial intelligence (AI) in detecting Marginal Bone Loss (MBL) around prosthetic crowns using 2-Dimentional radiographs. It also summarises the recent advances and future ...

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...

Classification of presence of missing teeth in each quadrant using deep learning artificial intelligence on panoramic radiographs of pediatric patients.

The Journal of clinical pediatric dentistry
Early tooth loss in pediatric patients can lead to various complications, making quick and accurate diagnosis essential. This study aimed to develop a novel deep learning model for classification of missing teeth on panoramic radiographs in pediatric...

Image segmentation of impacted mesiodens using deep learning.

The Journal of clinical pediatric dentistry
This study aimed to evaluate the performance of deep learning algorithms for the classification and segmentation of impacted mesiodens in pediatric panoramic radiographs. A total of 850 panoramic radiographs of pediatric patients (aged 3-9 years) was...

Automatic detection of the third molar and mandibular canal on panoramic radiographs based on deep learning.

Journal of stomatology, oral and maxillofacial surgery
PURPOSE: This study aims to develop a deep learning framework for the automatic detection of the position relationship between the mandibular third molar (M3) and the mandibular canal (MC) on panoramic radiographs (PRs), to assist doctors in assessin...

A fully automated classification of third molar development stages using deep learning.

Scientific reports
Accurate classification of tooth development stages from orthopantomograms (OPG) is crucial for dental diagnosis, treatment planning, age assessment, and forensic applications. This study aims to develop an automated method for classifying third mola...

Identification of dental implant systems from low-quality and distorted dental radiographs using AI trained on a large multi-center dataset.

Scientific reports
Most artificial intelligence (AI) studies have attempted to identify dental implant systems (DISs) while excluding low-quality and distorted dental radiographs, limiting their actual clinical use. This study aimed to evaluate the effectiveness of an ...