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Each row is one question a systematic review asked: who, what, compared with what, and which outcome, with the effect it found and how certain that is. Words match anywhere in the field.
555 questions in 21 reviews · intervention: Caries detection/diagnosis · outcome domain: Diagnostic accuracy
current versionsNo studies 19 · 3.4%Ungraded 489 · 88.1%Very low 17 · 3.1%Low 23 · 4.1%Moderate 7 · 1.3%High 0 · 0%
Ungraded means an effect was reported without a GRADE rating; it is not a gap. No studies means the review found nothing to answer the question. The six categories are a display order, not a score.
Intervention categories, outcome domains and clusters are a proposed key pending human validation. Clear all filters
| Question | Effect | Evidence | Status / GRADE |
|---|---|---|---|
Quantitative light-induced fluorescence (QLF) vs Reference standard (histology; some ICDAS/radiography) Occlusal caries detection: specificity · Extracted human teeth (in vitro); permanent and primary teeth, occlusal surfaces · Primary dentition Diagnostic accuracy of quantitative light-induced fluorescence in detecting caries of various types and… (2025) | Specificity 0.81 | 2 studies | Ungraded |
Intervention NR Sensitivity · Imaging modality: Bitewing radiographs Examining the diagnostic accuracy of artificial intelligence for detecting dental caries across a range of… (2025) | Sensitivity 0.81 [0.72, 0.91] | 5 studies | Ungraded |
Artificial intelligence algorithms for caries detection vs Dental expert or visual-tactile/clinical assessment as reference standard Diagnostic odds ratio · Dental images or diagnostic tests for dental caries detection · Overall (all imaging modalities pooled) Examining the diagnostic accuracy of artificial intelligence for detecting dental caries across a range of… (2025) | DOR 70.9 [44.9, 111.9] | 20 studies | Ungraded |
Intervention NR Specificity · Imaging modality: Bitewing radiographs Examining the diagnostic accuracy of artificial intelligence for detecting dental caries across a range of… (2025) | Specificity 0.89 [0.84, 0.95] | 5 studies | Ungraded |
Quantitative light-induced fluorescence (QLF) vs Reference standard (ICDAS II visual examination, ADA classification, bitewing radiography) Occlusal caries detection: specificity · Patients (in vivo); permanent and primary teeth, occlusal surfaces · Overall (all dentition) Diagnostic accuracy of quantitative light-induced fluorescence in detecting caries of various types and… (2025) | Specificity 0.82 | 4 studies | Ungraded |
Teledentistry (index test): dental caries diagnosis from photographs taken with DSLR or smartphone cameras; store-and-forward vs Visual/clinical dental examination (reference standard) Intra-examiner reliability · Children and adults with primary or permanent dentition undergoing dental caries assessment · Cross-sectional diagnostic accuracy (index test vs reference standard, in-vivo), Overall (studies reporting intra-examiner reliability; narrative synthesis) Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Intra-examiner reliability (kappa) reported in 6 studies, ranging from 0.52 to 1.00. No pooled estimate. | 6 studies | Ungraded |
Teledentistry diagnosis using DSLR or smartphone extra-oral photographs vs Visual or clinical examination Positive predictive value for dental caries diagnosis · Children and adults with primary or permanent dentition · Overall Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | no estimate extracted | 10 studies | Ungraded |
Teledentistry diagnosis using DSLR or smartphone extra-oral photographs vs Visual or clinical examination Negative predictive value for dental caries diagnosis · Children and adults with primary or permanent dentition · Overall Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | no estimate extracted | 10 studies | Ungraded |
Teledentistry (index test): dental caries diagnosis from photographs taken with DSLR or smartphone cameras; store-and-forward vs Visual/clinical dental examination (reference standard) Overall diagnostic accuracy (agreement) · Children and adults with primary or permanent dentition undergoing dental caries assessment · Cross-sectional diagnostic accuracy (index test vs reference standard, in-vivo), Overall (studies reporting accuracy; narrative synthesis) Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Accuracy 92.9% to 97.6% | 5 studies | Ungraded |
Teledentistry (index test): dental caries diagnosis from photographs taken with DSLR or smartphone cameras; store-and-forward vs Visual/clinical dental examination (reference standard) Specificity · Children and adults with primary or permanent dentition undergoing dental caries assessment · Cross-sectional diagnostic accuracy (index test vs reference standard, in-vivo), Overall (studies reporting specificity; narrative synthesis) Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Specificity ranged from 83% to 100% across studies (reported in 13 of 19 studies). No pooled estimate; meta-analysis not performed. | 13 studies | Ungraded |
Teledentistry (index test): dental caries diagnosis from photographs taken with DSLR or smartphone cameras; store-and-forward vs Visual/clinical dental examination (reference standard) Positive predictive value · Children and adults with primary or permanent dentition undergoing dental caries assessment · Cross-sectional diagnostic accuracy (index test vs reference standard, in-vivo), Overall (studies reporting PPV; narrative synthesis) Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | PPV 41.8% to 99% | 10 studies | Ungraded |
Teledentistry (index test): dental caries diagnosis from photographs taken with DSLR or smartphone cameras; store-and-forward vs Visual/clinical dental examination (reference standard) Sensitivity · Children and adults with primary or permanent dentition undergoing dental caries assessment · Cross-sectional diagnostic accuracy (index test vs reference standard, in-vivo), Overall (studies reporting sensitivity; narrative synthesis) Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Sensitivity Overall 48% to 98.3% across 13 studies; sensitivity is lesion-stage dependent: Kohara reported <40% for initial/moderate caries (75-100% for extensive) and early enamel lesions were less sensitive | 13 studies | Ungraded |
Teledentistry (index test): dental caries diagnosis from photographs taken with DSLR or smartphone cameras; store-and-forward vs Visual/clinical dental examination (reference standard) Inter-examiner reliability · Children and adults with primary or permanent dentition undergoing dental caries assessment · Cross-sectional diagnostic accuracy (index test vs reference standard, in-vivo), Overall (studies reporting inter-examiner reliability; narrative synthesis) Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Inter-examiner reliability (kappa) reported in 13 studies, ranging from 0.44 to 0.91. No pooled estimate. | 13 studies | Ungraded |
Teledentistry (index test): dental caries diagnosis from photographs taken with DSLR or smartphone cameras; store-and-forward vs Visual/clinical dental examination (reference standard) Negative predictive value · Children and adults with primary or permanent dentition undergoing dental caries assessment · Cross-sectional diagnostic accuracy (index test vs reference standard, in-vivo), Overall (studies reporting NPV; narrative synthesis) Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Negative predictive value reported in 10 of 19 studies; per-study values ranged from about 31% to 99.5% (Table 2). No pooled estimate. | 10 studies | Ungraded |
Teledentistry diagnosis using DSLR or smartphone extra-oral photographs vs Visual or clinical examination Sensitivity for dental caries diagnosis · Children and adults with primary or permanent dentition · Overall Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Sensitivity Overall 48% to 98.3% across 13 studies; sensitivity is lesion-stage dependent: Kohara reported <40% for initial/moderate caries (75-100% for extensive) and early enamel lesions were less sensitive | 13 studies | Ungraded |
Intervention NR Comparable diagnostic accuracy (photographic vs visual examination) · Overall narrative conclusion across included studies Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | Study conclusion (narrative) 17 of 19 studies concluded photographic diagnostic accuracy comparable to visual caries assessment | 19 studies | Ungraded |
Teledentistry diagnosis using DSLR or smartphone extra-oral photographs vs Visual or clinical examination Specificity for dental caries diagnosis · Children and adults with primary or permanent dentition · Overall Teledentistry accuracy for caries diagnosis: a systematic review of in-vivo studies using extra-oral… (2024) | no estimate extracted | 13 studies | Ungraded |
Visual or visual-tactile classification (e.g., ICDAS, ERK) vs Reference standard (histology, operative excavation, or enhanced visual examination) Sensitivity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 1: fully within-person comparison (studies evaluating >=3 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity 0.82 [0.73, 0.89] | 19 studies · 2849 participants | Ungraded |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Caries detection accuracy on intraoral images · Dental images of human beings · Kühnisch et al., 2022; convolutional neural networks Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 93.3 | 1 study · 2417 participants | Ungraded |
Intervention NR Difference in summary sensitivity (NMA, Analysis 2) · Electrical conductance vs Fluorescence Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity difference (95% CrI) 0.06 [-0.09, 0.18] | NR | Ungraded |
Intervention NR Difference in summary specificity (NMA, Analysis 2) · Fluorescence vs Transillumination Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity difference (95% CrI) 0.01 [-0.10, 0.15] | NR | Ungraded |
Intervention NR Difference in summary sensitivity (NMA, Analysis 2) · Fluorescence vs Transillumination Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity difference (95% CrI) -0.01 [-0.12, 0.13] | NR | Ungraded |
Transillumination and OCT vs Reference standard (histology, operative excavation, or enhanced visual examination) Specificity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 2: network meta-analysis (all studies evaluating >=2 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity 0.82 [0.68, 0.91] | 64 studies · 24567 participants | Low |
Fluorescence-based devices vs Reference standard (histology, operative excavation, or enhanced visual examination) Specificity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 1: fully within-person comparison (studies evaluating >=3 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity 0.88 [0.78, 0.94] | 19 studies · 2849 participants | Ungraded |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Caries detection accuracy in unrestored molars and premolars · Dental images of human beings · Duong et al., 2021; support vector machine Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 92.37 | 1 study · 620 participants | Ungraded |
Visual or visual-tactile classification (e.g., ICDAS, ERK) vs Reference standard (histology, operative excavation, or enhanced visual examination) Specificity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 2: network meta-analysis (all studies evaluating >=2 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity 0.81 [0.73, 0.87] | 64 studies · 24567 participants | Low |
Intervention NR Difference in summary sensitivity (NMA, Analysis 2) · Imaging vs Transillumination Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity difference (95% CrI) -0.27 [-0.40, -0.12] | NR | Ungraded |
Intervention NR Difference in summary specificity (NMA, Analysis 2) · Electrical conductance vs Imaging Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity difference (95% CrI) -0.16 [-0.45, 0.02] | NR | Ungraded |
Intervention NR Difference in summary sensitivity (NMA, Analysis 2) · Imaging vs Visual Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity difference (95% CrI) -0.34 [-0.42, -0.23] | NR | Ungraded |
Fluorescence-based devices vs Reference standard (histology, operative excavation, or enhanced visual examination) Sensitivity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 2: network meta-analysis (all studies evaluating >=2 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity 0.76 [0.68, 0.82] | 64 studies · 24567 participants | Low |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Proximal caries detection accuracy · Dental images of human beings · Casalegno et al., 2018; CNN Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 85.6 | 1 study · 217 participants | Ungraded |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Occlusal caries detection accuracy · Dental images of human beings · Moutselos et al., 2019; MASK R-CNN; worst class Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 66.7 | 1 study · 88 participants | Ungraded |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Dental caries detection accuracy · Dental images of human beings · Mayank et al., 2017; F-CNN Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 70 | 1 study · 3000 participants | Ungraded |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Premolar caries detection accuracy · Dental images of human beings · Lee et al., 2018; CNN Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 88 | 1 study · 3000 participants | Ungraded |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Proximal caries detection accuracy · Dental images of human beings · Devito et al., 2008; hidden-layer perceptron with backpropagation Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 88.4 | 1 study · 160 participants | Ungraded |
Visual or visual-tactile classification (e.g., ICDAS, ERK) vs Reference standard (histology, operative excavation, or enhanced visual examination) Sensitivity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 2: network meta-analysis (all studies evaluating >=2 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity 0.83 [0.77, 0.87] | 64 studies · 24567 participants | Low |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Dental caries detection accuracy · Dental images of human beings · Zanella-Calzada et al., 2018; ANN Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 69 | 1 study · 189 participants | Ungraded |
Intervention NR Difference in summary sensitivity (NMA, Analysis 2) · Fluorescence vs Imaging Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity difference (95% CrI) 0.26 [0.15, 0.37] | NR | Ungraded |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Molar and premolar caries detection accuracy · Dental images of human beings · Lee et al., 2018; CNN Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 82 | 1 study · 3000 participants | Ungraded |
Electrical conductance or impedance vs Reference standard (histology, operative excavation, or enhanced visual examination) Sensitivity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 2: network meta-analysis (all studies evaluating >=2 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity 0.83 [0.66, 0.92] | 64 studies · 24567 participants | Low |
Intervention NR Difference in summary sensitivity (NMA, Analysis 2) · Electrical conductance vs Visual Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity difference (95% CrI) 0.00 [-0.17, 0.11] | NR | Ungraded |
Machine-learning algorithms (deep learning: CNN/FCNN, ANN, backpropagation neural network, SVM, ADA-NN, Mask R-CNN) applied as an index test to detect dental caries vs Different machine-learning algorithms compared with one another / against the reference caries diagnosis Diagnostic accuracy for root caries detection · Dental radiographic/intraoral images of human teeth (X-ray and photographic) · Root caries Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) | Accuracy 97.1 | 1 study | Ungraded |
Intervention NR Difference in summary specificity (NMA, Analysis 2) · Electrical conductance vs Fluorescence Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity difference (95% CrI) -0.11 [-0.40, 0.07] | NR | Ungraded |
Fluorescence-based devices vs Reference standard (histology, operative excavation, or enhanced visual examination) Sensitivity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 1: fully within-person comparison (studies evaluating >=3 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity 0.71 [0.59, 0.81] | 19 studies · 2849 participants | Ungraded |
Intervention NR Difference in summary specificity (NMA, Analysis 2) · Imaging vs Transillumination Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity difference (95% CrI) 0.07 [-0.03, 0.20] | NR | Ungraded |
Imaging (analog or digital radiographs) vs Reference standard (histology, operative excavation, or enhanced visual examination) Specificity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 2: network meta-analysis (all studies evaluating >=2 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity 0.89 [0.83, 0.93] | 64 studies · 24567 participants | Low |
Imaging (analog or digital radiographs) vs Reference standard (histology, operative excavation, or enhanced visual examination) Sensitivity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 1: fully within-person comparison (studies evaluating >=3 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity 0.48 [0.35, 0.62] | 19 studies · 2849 participants | Ungraded |
Intervention NR Difference in summary specificity (NMA, Analysis 2) · Electrical conductance vs Transillumination Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity difference (95% CrI) -0.09 [-0.38, 0.12] | NR | Ungraded |
Transillumination and OCT vs Reference standard (histology, operative excavation, or enhanced visual examination) Sensitivity for detecting enamel caries · Asymptomatic children or adults suspected of enamel caries (clinical studies); extracted teeth (in vitro studies) · Analysis 2: network meta-analysis (all studies evaluating >=2 index tests) Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Sensitivity 0.76 [0.63, 0.86] | 64 studies · 24567 participants | Low |
Intervention NR Difference in summary specificity (NMA, Analysis 2) · Fluorescence vs Imaging Enamel Caries Detection and Diagnosis: An Analysis of Systematic Reviews. (2022) | Specificity difference (95% CrI) -0.05 [-0.14, 0.02] | NR | Ungraded |