Objectives Despite deep learning's wide adoption in dental artificial intelligence (AI)
research, researchers from other dental fields and, more so, dental professionals may find it …

Artificial intelligence has made substantial progress in medicine. Automated dental imaging
interpretation is one of the most prolific areas of research using AI. X-ray and infrared …

The integration of Computer-Aided Diagnosis (CAD) with Large Language Models (LLMs)
presents a promising frontier in clinical applications, notably in automating diagnostic …

Third molar impacted teeth are a common issue with all ages, possibly causing tooth decay,
root resorption, and pain. This study was aimed at develo** a computer-assisted detection …

Automated dental imaging interpretation is one of the most prolific areas of research using
artificial intelligence. X-ray imaging systems have enabled dental clinicians to identify dental …

The Integration of machine learning and traditional image processing in dentistry has
resulted in many applications like automatic teeth identification and numbering, caries …

Featured Application Convolutional Neural Network (CNN) models are capable of learning
complex patterns and features from images. An automatic teeth segmentation CNN model …

Due to the necessity for precise treatment planning, the use of panoramic X-rays to identify
different dental diseases has tremendously increased. Although numerous ML models have …

Objective: This work aimed to detect automatically periapical lesion on panoramic
radiographs (PRs) using deep learning. Methods: 454 objects in 357 PRs were anonymized …

Objectives The objective was to evaluate the robustness of deep learning (DL)-based
encoder–decoder convolutional neural networks (ED-CNNs) for segmenting …