Table 2.
Algorithm performance.
| AUC | Sensitivity | Specificity | Accuracy | |
|---|---|---|---|---|
| Internal validation dataset (n = 401) | 0·983 (0·973–0·991) | 94·9% (91·5–97·8) | 88·7% (84·5–92·6) | 91·5% (88·8–94·3) |
| Secondary analysis* (n = 170) | 0·995 (0·988–0·999) | 97·4% (93·2–100·0) | 93·5% (88·2–97·9) | 95·3% (91·8–98·2) |
| External validation dataset (n = 402) | 0·935 (0·910–0·957) | 89·6% (84·7–94·2) | 80·6% (75·7–85·3) | 84·1% (80·3–87·6) |
| Clinical validation dataset (n = 666) | 0·970 (0·957–0·981) | 91·0% (87·9–94·1) | 93·5% (90·9–96·0) | 92·3% (90·2–94·3) |
Data in parentheses are 95% CIs.
⁎
In the secondary analysis, only photographs of early-stage oral cavity squamous cell carcinoma (lesion's diameter less than two centimetres) and random selected negative controls in the internal validation dataset were used.