evidencegaps
Primary study · included by 1 review

Tooth caries classification with quantitative light-induced fluorescence (QLF) images using convolutional neural network for permanent teeth in vivo.

Park 2023 · Park Eun Young, Jeong Sungmoon, Kang Sohee, et al. · BMC oral health · 2023

Included by

Artificial intelligence for binary dental caries diagnosis using intraoral images and dental radiographs: a systematic review and meta-analysis.
Non-Cochrane · DTA · 2026 · cited as Park 2023 · Supplementary Table S1; Fig. 2
Outcome this study informsPooled effectEvidenceCertainty
Pooled sensitivity
AI (deep learning) models for binary caries classification vs Reference standard (expert examiners or clinical/diagnostic reference)
Sensitivity 0.86 [0.82, 0.89]13 studiesGRADE not reported

1 including review in total.