Table 3 Accuracies of the tenfold individual feature models
No | Feature input | ML algorithm | Mean Acc | Standard deviation | Max | Min |
|---|---|---|---|---|---|---|
1 | Minimal lumen diameter | Scale SVM | 63.43 | 6.46 | 71.57 | 53.92 |
2 | Proximal radius rapport | Poly SVM | 64.31 | 5.14 | 71.57 | 53.92 |
3 | Radius rapport | Poly SVM | 65.59 | 4.39 | 71.57 | 54.9 |
4 | Percentage diameter reduction | Poly SVM | 66.18 | 1.4 | 68.63 | 63.73 |
5 | Mean radius | Decision Tree | 62.75 | 6.75 | 71.57 | 53.92 |
6 | Minimum lumen radius | Naive Bayes | 60.59 | 6.06 | 71.57 | 53.92 |
7 | Weight | Naive Bayes | 64.51 | 4.27 | 69.61 | 53.92 |
8 | Mean lumen radius for stenosis region | Scale SVM | 67.35 | 2.01 | 71.57 | 64.71 |
9 | Mean radius per length | Scale SVM | 61.76 | 6 | 71.57 | 53.92 |
10 | Maximum radius rapport | K-nearest neighbors | 64.31 | 5.79 | 71.57 | 53.92 |
11 | Stenosis lesion length | Poly SVM | 66.27 | 1.53 | 68.63 | 63.73 |
12 | Hematocrit level | Decision Tree | 62.25 | 6.59 | 71.57 | 53.92 |
13 | Interventricular septum | Scale SVM | 64.61 | 4.54 | 71.57 | 53.92 |
14 | Maximum lumen radius | AdaBoost | 65.39 | 2.98 | 69.61 | 58.82 |
15 | Smoking | Scale SVM | 55.5 | 4.8 | 59.8 | 47.52 |
16 | Dyslipidemia | Naive Bayes | 54.71 | 6.51 | 60.54 | 43.88 |
17 | AHT | Scale SVM | 53.53 | 3.72 | 56.86 | 47.34 |
18 | Diastolic pattern | Naive Bayes | 52.88 | 4.44 | 56.86 | 45.5 |
19 | Age | Linear SVM | 51.17 | 3.64 | 54.43 | 45.11 |
20 | Diabetes | Random Forest 60 | 50.33 | 4.01 | 53.92 | 43.66 |
21 | Distal area | Decision Tree | 50.53 | 3.79 | 53.92 | 44.22 |
22 | Echo EF | Poly SVM | 49.59 | 4.83 | 53.92 | 41.56 |
23 | Hb | Linear SVM | 48.72 | 5.8 | 53.92 | 39.06 |
24 | Hight | Random Forest 60 | 51.43 | 2.78 | 53.92 | 46.8 |
25 | Proximal area | Linear SVM | 50.52 | 3.8 | 53.92 | 44.2 |
26 | Sex | Linear SVM | 48.59 | 5.94 | 53.92 | 38.7 |