Table 1 Confusion matrix to evaluate accuracy, precision, and recall of the algorithm model
Predicted severity | Actual numbers in the test dataset | Total | ||
|---|---|---|---|---|
Score 1 | Score 2 | Score 3 | ||
A Accuracy, precision, and recall of our algorithm model | ||||
 Score 1 | 32 | 1 | 1 | 34 |
 Score 2 | 4 | 85 | 2 | 91 |
 Score 3 | 7 | 7 | 98 | 112 |
 Total | 43 | 93 | 101 | 237 |
 Precision | 94.1% | 93.4% | 87.5% |  |
 Recall | 74.4% | 91.4% | 97.0% |  |
 F1-Measure | 0.831 | 0.924 | 0.920 |  |
 Total prediction accuracy | - | - | - | 90.7% |
B Accuracy, Precision, and Recall of Physicians | ||||
 Score 1 | 33 | 3 | 0 | 36 |
 Score 2 | 5 | 83 | 6 | 94 |
 Score 3 | 5 | 7 | 95 | 107 |
 Total | 43 | 93 | 101 | 237 |
 Precision | 91.7% | 88.3% | 88.8% |  |
 Recall | 76.7% | 89.3% | 94.1% |  |
 F1-Measure | 0.835 | 0.888 | 0.914 |  |
 Total prediction accuracy | - | - | - | 89.0% |