+ HEALTH The accurate identification of children with refractory Mycoplasma pneumoniae pneumonia (RMPP) remains challe…± LABOR The advent of automation, artificial intelligence and disruptive technologies has affected the role of the Hu…+ ENTERTAINMENT This paper provides a systematic exploration of Artificial Intelligence (AI) for music generation within a cl…− POLICY Generative AI (GenAI) has shifted AI capabilities from discriminative prediction to creative interaction, off…± CLIMATE Automation and sustainability are closely intertwined in the evolution of Industry 4.0 and 5.0, where artific…+ ENTERTAINMENT This article aims to investigate the factors that affect behavioural intention (BI) and user behaviour (UB) a…+ CLIMATE With accelerating climate change and rising global energy consumption, the application of artificial intellig…− HEALTH Biases in medical artificial intelligence (AI) arise and compound throughout the AI lifecycle. These biases c…
TruaceTracing the truth around AISunday, July 19, 2026
Subscribe
Health·G Space·Evidence-backed gain·Published 2026-07-18

Effect of AI-assisted caries annotation on dental students' performance in caries detection on panoramic radiographs

Dental caries remains one of the most prevalent oral diseases globally. The integration of artificial intelligence (AI) into dental radiographic interpretation, particularly for caries detection, has expanded rapidly. AI-assisted caries annotation may help dental students identify carious lesions on panoramic radiographs-a commonly used diagnostic tool for evaluating teeth and surrounding structures-thereby improving diagnostic accuracy, efficiency, and confidence. This study aimed to assess the effect of AI-ass…

TRV-2026-0258Peer-reviewedPermanent record — cite & verify
Effect of AI-assisted caries annotation on dental students' performance in caries detection on panoramic radiographs

"NMCP Installs New, Safer Dental Equipment" by NavyMedicine is marked with Public Domain Mark 1.0. To view the terms, visit https://creativecommons.org/publicdomain/mark/1.0/.

The quick read

In a study published July 16, 2026, 40 fourth-year dental students interpreted 40 panoramic radiographs first without assistance and then one month later with AI-assisted caries annotation. The radiographs contained multistage lesions verified by bite-wing radiographs, and students recorded lesion location, depth, time, and confidence.

The results matter because panoramic interpretation is a core competency where students traditionally miss early lesions, and the observed gains in sensitivity and confidence suggest AI annotation could serve as an educational adjunct. What remains uncertain from the text is whether improvements persist without AI, transfer to real patient care, or generalize beyond the single institution and 40-student sample.

Main points
  • Study used 50 panoramic radiographs with multistage carious lesions verified by bite-wing radiographs as the gold standard, with 40 used for testing.
  • 40 fourth-year dental students completed Session 1 on unannotated radiographs and Session 2 one month later with AI-assisted annotation.
  • Sensitivity rose from 0.35 to 0.67 and miss rate decreased from 0.65 to 0.33 with AI assistance.
  • Calibration included ten sets of unannotated and AI-annotated radiographs before testing.
Gain

AI-assisted caries annotation increased dental students' diagnostic accuracy, sensitivity, and confidence while reducing interpretation time on panoramic radiographs.

The rundown

The experiment was structured as two sessions one month apart using the same 40 radiographs, with location and depth of detected caries, diagnostic time, and self-reported confidence on a 0-10 scale recorded per radiograph.

Statistical comparison used paired t-tests or Wilcoxon tests and reported improvements across accuracy, balanced accuracy from 0.65 to 0.83, precision from 0.33 to 0.77, and negative predictive value from 0.95 to 0.98.

Sources

Reader signal

How should this claim be treated?

The debate