Primary study · included by 1 review

Devlin 2021

ProbableThe reviews cited this study without a PMID, DOI or NCT, so it is matched by first author and year. Two different studies by the same author in the same year could be merged here.

Trial PICO

Not extracted yet. Trial-level population, intervention, comparator, outcomes and design will appear here after the trial extraction run. Until then, the reviews below describe the study.

Results

Not extracted yet. Per-trial results (events, means, effect and weight as each review's forest plot reports them) will appear here after the trial extraction run.

Included by

Accuracy of artificial intelligence in caries detection: a systematic review and meta-analysis.

Non-Cochrane · DTA · 2025 · cited as Devlin 2021 · Table 2 (No. 15); Table 3 (Sl 15); Reference [31]; pooled in sensitivity meta-analysis (Table 5)

Outcome this study informs	Pooled effect	Evidence	Certainty
Sensitivity AI systems for caries detection/segmentation on dental X-ray images (predominantly convolutional neural networks; also ANNs, DNNs, DCNN, FCNN, SVMs, decision trees, random forests; e.g. EfficientNet, ResNet, AlexNet) vs Human dentists / trained dental professionals or traditional radiographic interpretation (reference standard / reference models)	OR 1.258 [0.493, 2.540]	9 studies · 17190 participants	Ungraded

1 including review in total.