Primary study · included by 1 review
Intelligent deep learning supports biomedical image detection and classification of oral cancer
Chen 2024 · Chen Rongcan, Wang Qinglian, Huang Xiaoyuan · Technology and Health Care · 2024
Included by
| Outcome this study informs | Pooled effect | Evidence | Certainty |
|---|---|---|---|
Diagnostic accuracy AI models for oral cancer diagnosis or risk assessment (image-based and text-based) vs Reference standard (histopathology where available, otherwise expert clinical diagnosis) | Pooled accuracy (proportion) 0.89 [0.83, 0.95] | 11 studies | GRADE not reported |
Diagnostic sensitivity AI models for oral cancer diagnosis or risk assessment (image-based and text-based) vs Reference standard (histopathology where available, otherwise expert clinical diagnosis) | Pooled sensitivity (proportion) 0.90 [0.81, 0.98] | 13 studies | GRADE not reported |
Diagnostic specificity AI models for oral cancer diagnosis or risk assessment (image-based and text-based) vs Reference standard (histopathology where available, otherwise expert clinical diagnosis) | Pooled specificity (proportion) 0.89 [0.84, 0.95] | 14 studies | GRADE not reported |
1 including review in total.