ArticleInternational journal of dentistry2024
Dental Cavity Grading: Comparing Algorithm Reliability and Agreement with Expert Evaluation.
Article in International journal of dentistry, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Evaluating a Novel Visualization Device for Improving File Insertion Accuracy During Root Canal Treatment.European journal of dentistry · 2026Article
- Automated evaluation of dental cavity preparation quality using deep learning and anatomically informed geometric analysis.Frontiers in artificial intelligence · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Aim: The current study introduces a novel, algorithm-based software developed to objectively evaluate dental cavity preparations. The software aims to provide an alternative or complement to traditional, subjective assessment methods used in operative dentistry education. Materials and Methods: The software was tested on cavity preparations carried out by 70 participants on artificial molar teeth. These cavities were also independently assessed by an experienced academic panel. The software, using 3D imaging, calculated cavity dimensions and assigned an error score based on deviation from ideal measurements. Statistical analyses included sensitivity, specificity, positive predictive value, negative predictive value, Cohen's kappa, the intraclass correlation coefficient (ICC3k), Spearman's rho, Kendall's tau correlation coefficients, and a confusion matrix. Result: The software demonstrated a high degree of accuracy and agreement with the panel assessments. The average software and panel scores were 64.1 and 60.91, respectively. Sensitivity (0.98) was high, specificity (0.55) was moderate, and the ICC3k value (0.857) indicated a strong agreement between the software and the panel. Further, Spearman's rho (0.73) and Kendall's tau (0.56) suggested a strong correlation between the two grading methods. Conclusion: The results support the algorithm-based software as a valid and reliable tool for dental cavity preparation assessments. The software's potential use in dental education is promising, though future research is necessary to validate and optimize this technology for wider application.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.