Table 6.
Statistical comparisons of reported model performance metrics, by AI/ML algorithm.
| AI/ML algorithm | Performance metrics: Mean (SD, n) |
|||
|---|---|---|---|---|
| AUC | Accuracy | Sensitivity | Specificity | |
| ANN | 0.81 (0.11, 56) | 87.6 (11.7, 14) | 70.69 (24.18, 15) | 88.4 (12.9, 15) |
| Bayesian | 0.81 (0.07, 8) | 84.1 (2.6, 4) | — | — |
| Boosting | 0.79 (0.07, 19) | 77.3 (7.1, 7) | 77.8 (5.36, 5) | 72.8 (11.7, 5) |
| Decision tree | 0.78 (0.1, 41) | 89 (—, 1) | 86.35 (16.05, 2) | 99.8 (0.4, 2) |
| Regression | 0.77 (0.07, 62) | 79 (8.7, 7) | 75.75 (11.28, 6) | 70.4 (14.6, 6) |
| SVM | 0.77 (0.11, 26) | 83.2 (10, 5) | 86.1 (7.34, 5) | 80.5 (16.1, 5) |
| ANOVA | P = .252 | P = .228 | P = .497 | P = .019 |
| Tukey Post Hoc Tests (stat. significant results) | — | — | — | — |
AI/ML, artificial intelligence/machine learning; ANN, artificial neural network; ANOVA, analysis of variance; AUC, area under curve; SD, standard deviation; SVM, support vector machine.