Primary study · included by 1 review
Application value of dual-sequence MRI based nomogram of radiomics and morphologic features in predicting tumor differentiation degree and lymph node metastasis of Oral squamous cell carcinoma.
Zheng 2025 · Zheng Bozhong, Yu Baoting, Zheng Xuewei, et al. · Frontiers in oncology · 2025
Included by
| 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 |
1 including review in total.