PubMed · 14963418
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G S Antonarakis. 2004-02-14. Consensus on training.. https://doi.org/10.1038/sj.bdj.4810977
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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.
Orthodontics has the potential to cause significant damage to hard and soft tissues. The most important aspect of orthodontic care is to have an extremely high standard of oral hygiene before and during orthodontic treatment. It is also essential that any carious lesions are dealt with before any active treatment starts. Root resorption is a common complication during orthodontic treatment but there is some evidence that once appliances are removed this resorption stops. Some of the risk pointers for root resorption are summarised. Soft tissue damage includes that caused by archwires but also the more harrowing potential for headgears to cause damage to eyes. It is essential that adequate safety measures are included with this type of treatment.
BACKGROUND AND OBJECTIVES: The intrinsic fluorescence of carious human teeth, of different stages of teeth demineralization, and the correspondence of such fluorescence to the mineral and organic distribution within the lesions were investigated. STUDY DESIGN/MATERIALS AND METHODS: Fluorescence spectra of teeth excited with 337 nm nitrogen laser were recorded. Spectra were obtained from healthy enamel, dentine, demineralized areas, and different carious stages of the teeth investigated. RESULTS: Spectra obtained from sound enamel consisted of one intensive peak at 480-500 nm and one secondary peak at 430-450 nm. In dentine, this secondary component had much higher intensity. Fluorescence spectra of normal teeth were similar to those of enamel layer. A significant decrease of the intensity of the fluorescence signal was observed in both cases-in demineralized teeth and in carious lesion. The appearance of a fluorescence peak in the red spectral region was observed in the spectra of the initial carious lesions. In the teeth demineralization process, we observed an increase of the relative fluorescence peak intensity at 430-450 nm related to thinned out of enamel. CONCLUSIONS: A differentiation between initial tooth demineralization and early stages of caries could be made by the laser-induced fluorescence spectroscopy method.