Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction: Occlusal caries detection accuracy
The review reported 66.7% accuracy for the worst class in Moutselos et al. (Ungraded).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Occlusal caries detection accuracy · Dental images of human beings · in-vitro dental images, Moutselos et al., 2019; MASK R-CNN; worst class The review reported 66.7% accuracy for the worst class in Moutselos et al. (Ungraded). Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) All outcomes | Accuracy 66.7 | 1 study · 88 participants | GRADE not reported |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Occlusal caries detection accuracy · Dental images of human beings · Switzerland, Casalegno et al., 2018; CNN The review reported 83.6% accuracy for occlusal caries in Casalegno et al. (Ungraded). Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) All outcomes | Accuracy 83.6 | 1 study · 217 participants | GRADE not reported |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Occlusal caries detection accuracy · Dental images of human beings · in-vitro dental images, Moutselos et al., 2019; MASK R-CNN; most common class The review reported 88.9% accuracy for the most common class in Moutselos et al. (Ungraded). Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) All outcomes | Accuracy 88.9 | 1 study · 88 participants | GRADE not reported |
Machine-learning algorithms for dental caries detection vs Different machine-learning algorithms for caries prediction Occlusal caries detection accuracy · Dental images of human beings · in-vitro dental images, Moutselos et al., 2019; MASK R-CNN; center pixel class The review reported 77.8% accuracy for the center pixel class in Moutselos et al. (Ungraded). Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. (2022) All outcomes | Accuracy 77.8 | 1 study · 88 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Uses of Different Machine Learning Algorithms for Diagnosis of Dental Caries. 2022 All outcomes | Not specified | 17 | Not applicable |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.