From: Machine learning assisted Cameriere method for dental age estimation
Method | ME ± SD | MAE ± SD | MSE ± SD | RMSE ± SD | R2 ± SD |
---|---|---|---|---|---|
Linear regression | 0.008 ± 0.052 (− 0.095–0.094) | 0.553 ± 0.026 (0.501–0.589) | 0.488 ± 0.063 (0.396–0.588) | 0.698 ± 0.045 (0.629–0.767) | 0.909 ± 0.012 (0.890–0.925) |
Support vector machine | 0.004 ± 0.063 (− 0.142–0.104) | 0.489 ± 0.030 (0.422–0.552) | 0.392 ± 0.049 (0.286–0.480) | 0.625 ± 0.039 (0.535–0.693) | 0.925 ± 0.011 (0.900–0.949) |
Random Forest | − 0.004 ± 0.046 (− 0.090–0.088) | 0.495 ± 0.024 (0.446–0.533) | 0.389 ± 0.039 (0.309–0.461) | 0.623 ± 0.032 (0.556–0.679) | 0.928 ± 0.009 (0.914–0.945) |
European formula | 0.592 ± 0.032 (0.532–0.654) | 0.846 ± 0.228 (0.801–0.891) | 0.755 ± 0.038 (0.684–0.829) | 0.869 ± 0.022 (0.827–0.911) | – |
Chinese formula | 0.386 ± 0.035 (0.322–0.450) | 0.812 ± 0.022 (0.530–0.655) | 0.890 ± 0.049 (0.796–0.997) | 0.943 ± 0.026 (0.892–0.999) | – |