Primary study · included by 1 review
Accuracy of convolutional neural networks-based automatic segmentation of pharyngeal airway sections according to craniofacial skeletal pattern.
Cho 2022 · Cho Ha-Nul, Gwon Eunseo, Kim Kyung-A, et al. · American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics · 2022
Included by
| Outcome this study informs | Pooled effect | Evidence | Certainty |
|---|---|---|---|
Recall (sensitivity) of AI segmentation AI-based (deep learning or machine learning) 3D segmentation vs Manual segmentation by human experts | Weighted mean 0.92 [0.87, 0.97] | 3 studies | GRADE not reported |
Dice similarity score Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.94 [0.91, 0.97] | 3 studies | GRADE not reported |
Precision of AI segmentation AI-based (deep learning or machine learning) 3D segmentation vs Manual segmentation by human experts | Weighted mean 0.95 [0.92, 0.97] | 3 studies | GRADE not reported |
Precision of AI segmentation AI-based (deep learning or machine learning) 3D segmentation vs Manual segmentation by human experts | Weighted mean 0.95 [0.93, 0.97] | 4 studies | GRADE not reported |
Dice similarity score Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.95 [0.92, 0.98] | 3 studies | GRADE not reported |
Precision of AI segmentation AI-based (deep learning or machine learning) 3D segmentation vs Manual segmentation by human experts | Weighted mean 0.96 [0.93, 0.99] | 3 studies | GRADE not reported |
Recall (sensitivity) Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.95 [0.92, 0.99] | 3 studies | GRADE not reported |
Recall (sensitivity) Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.93 [0.87, 0.99] | 3 studies | GRADE not reported |
Recall (sensitivity) of AI segmentation AI-based (deep learning or machine learning) 3D segmentation vs Manual segmentation by human experts | Weighted mean 0.94 [0.89, 0.98] | 4 studies | GRADE not reported |
Recall (sensitivity) of AI segmentation AI-based (deep learning or machine learning) 3D segmentation vs Manual segmentation by human experts | Weighted mean 0.94 [0.88, 1.0] | 3 studies | GRADE not reported |
Precision Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.96 [0.94, 0.98] | 3 studies | GRADE not reported |
Dice similarity score Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.95 [0.93, 0.98] | 3 studies | GRADE not reported |
Dice similarity score Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.94 [0.92, 0.97] | 4 studies | GRADE not reported |
Dice similarity score Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.94 [0.91, 0.96] | 3 studies | GRADE not reported |
Precision Automatic 3D segmentation by artificial intelligence (deep learning or machine learning) vs Manual segmentation by human experts | Weighted mean 0.95 [0.92, 0.97] | 3 studies | GRADE not reported |
1 including review in total.