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 …

Within the ever-growing healthcare industry, dental informatics is a burgeoning field of study.
One of the major obstacles to the health care system's transformation is obtaining …

Dental caries is the most prevalent chronic condition worldwide. Early detection can
significantly improve treatment outcomes and reduce the need for invasive procedures …

Objectives In this pilot study, we applied deep convolutional neural networks (CNNs) to
detect caries lesions in Near-Infrared-Light Transillumination (NILT) images. Methods 226 …

Objectives The aim of the present prospective multicenter clinical study was to compare the
detection of proximal caries with near-infrared light reflection (NILR) versus bitewing …

Aim This systematic review and meta-analysis aimed to assess the diagnostic accuracy and
reliability of commonly used caries detection methods for proximal caries diagnostics. Visual …

A shift in caries prevalence from occlusal surfaces to approximal surfaces has been
demonstrated by epidemiological studies. Two recent meta-analyses evaluated the …

Objectives To assess the validity of an intraoral scanner system featuring near-infrared (NIR)
transillumination to aid the detection of proximal caries lesions, and to compare the …

The aim of this in vitro study was to systematically investigate new caries diagnostic tools,
including three intraoral scanners, and compare them to established diagnostic methods …

Objective To compare near infrared transillumination device, DIAGNOcam (DC) and
bitewing radiography (BW) for the detection of proximal caries. Materials and methods This …