PubMed · 756501
The source did not provide an abstract. Follow the original record for more information.
Explore connections, maps & timelines
P Riethe. 1978. [Caries prevention].. https://pubmed.ncbi.nlm.nih.gov/756501/
Cite the original work for its findings. Save a collection to share your selection of sources.
KEEP EXPLORING
Artificial intelligence (AI) has been proposed as a tool to improve dental caries detection across imaging modalities; however, its clinical value remains uncertain. This umbrella review aimed to synthesize and critically appraise systematic reviews evaluating AI for caries detection and diagnosis. An umbrella review was conducted following PRIOR guidance (PROSPERO CRD420261340728). Searches were performed in MEDLINE, Embase, Scopus, Web of Science, and Google Scholar up to 15 March 2026. Methodological quality was assessed using AMSTAR 2, and overlap of primary studies was quantified using the corrected covered area (CCA). Seventeen systematic reviews were included, of which five reported diagnostic test accuracy meta-analyses using bivariate or HSROC models. Across these meta-analyses, pooled sensitivity ranged from 0.76 to 0.94 and specificity from 0.85 to 0.91. Most systems were based on deep learning models applied to bitewing radiographs and intraoral photographs. However, substantial heterogeneity was observed in imaging modalities, lesion thresholds, analytical tasks, and evaluation metrics. In addition, a high degree of overlap across reviews and recurrent methodological limitations, including reliance on retrospective datasets, limited external validation, and inconsistent reporting, substantially weaken the reliability of the evidence. Although AI models demonstrate high diagnostic performance under experimental conditions, current evidence does not support their use as stand-alone diagnostic tools. Their clinical applicability remains limited, and implementation should be restricted to decision-support contexts until robust prospective validation demonstrates meaningful impact on clinical decision-making and patient outcomes.
The Food and Drug Administration (FDA) is adopting as a final rule, without change, the provisions of the interim final rule that amended the regulation authorizing a health claim on sugar alcohols and dental caries, i.e., tooth decay, to include the sugar D-tagatose as a substance eligible for the dental caries health claim. FDA is taking this action to complete the rulemaking initiated with the interim final rule.
A basic understanding of the light-scattering processes that take place inside the dental tissue (either sound or carious) is obtained both with measurements of the photon path-length distribution of light inside such media and with Monte Carlo simulations. Furthermore, the following is investigated: the correlations between different momenta of the photon path-length distribution of light inside caries lesions, the fluorescence loss determined with quantitative light-induced fluorescence, and/or the demineralization and depth of caries lesions determined with transversal microradiography. It is concluded that (i) the light paths inside both carious and sound enamel are considerably influenced by the refractive-index contrast at the tooth surface; (ii) contrary to a previous hypothesis, the fluorescence loss is larger in lesions in which the average photon path length is longer; (iii) very good correlations are obtained between the optical characteristics and the physical parameters of lesions when the optical measurements are performed such that there is high refractive contrast at the tooth surface.