evidencegaps
Primary study · included by 1 review

CDSNet: An automated method for assessing growth stages from various anatomical regions in lateral cephalograms based on deep learning

Zhang 2024 · Zhang Yuchen, Lu Zhen, Zhou Jianglin, et al. · Journal of the World Federation of Orthodontists · 2025

Included by

Artificial intelligence for predicting the pubertal growth spurt using cephalometric and hand-wrist radiographs: a systematic review and meta-analysis.
Non-Cochrane · DTA · 2026 · cited as Zhang 2024 · Table 1; reference 43
Outcome this study informsPooled effectEvidenceCertainty
Pooled accuracy
AI models (best model per study) applied to lateral cephalometric and/or hand-wrist radiographs to identify the pubertal growth spurt (three-class pre-spurt, spurt, post-spurt scheme) vs Reference staging by expert assessment (CVM, Fishman SMI, Grave and Brown, DRU or other validated standards)
Accuracy (proportion) 0.83 [0.76, 0.89]21 studiesGRADE not reported

1 including review in total.