Primary study · included by 2 reviews
Magnetic resonance imaging-based radiomics and deep learning models for predicting lymph node metastasis of squamous cell carcinoma of the tongue.
Wang D 2024 · Wang Dawei, He Xiao, Huang Chunming, et al. · Oral surgery, oral medicine, oral pathology and oral radiology · 2024
Included by
The review does not say which of its outcomes this study informs.
| Outcome this study informs | Pooled effect | Evidence | Certainty |
|---|---|---|---|
Sensitivity AI-based algorithms (radiomics machine learning or deep learning) applied to MRI vs Histopathology reference standard (cervical lymph node status) | Sensitivity 0.71 | 7 studies | GRADE not reported |
Sensitivity AI-based algorithms (radiomics machine learning or deep learning) applied to MRI vs Histopathology reference standard (cervical lymph node status) | Sensitivity 0.72 [0.62, 0.80] | 7 studies · 548 participants | Low |
Sensitivity AI-based algorithms (radiomics machine learning or deep learning) applied to MRI vs Histopathology reference standard (cervical lymph node status) | Sensitivity 0.725 | 6 studies | GRADE not reported |
2 including reviews in total.