Research Article
Optimal Deep Learning Enabled Prostate Cancer Detection Using Microarray Gene Expression
Table 2
Result analysis of proposed AIFSDL-PCD model.
| No. of iterations | Sensitivity | Specificity | Precision | Accuracy | F-score |
| Iteration 1 | 97.75 | 97.26 | 96.87 | 97.47 | 97.58 | Iteration 2 | 97.25 | 97.30 | 96.69 | 96.83 | 97.48 | Iteration 3 | 97.59 | 97.21 | 97.34 | 97.41 | 97.06 | Iteration 4 | 97.49 | 97.10 | 96.92 | 97.18 | 97.07 | Iteration 5 | 97.11 | 96.60 | 96.90 | 96.69 | 97.22 | Iteration 6 | 97.43 | 96.92 | 97.39 | 97.27 | 96.89 | Iteration 7 | 96.87 | 97.27 | 97.34 | 97.06 | 97.75 | Iteration 8 | 97.18 | 97.37 | 97.43 | 97.34 | 97.71 | Iteration 9 | 96.51 | 97.78 | 97.25 | 97.41 | 97.51 | Iteration 10 | 97.28 | 97.66 | 97.23 | 97.28 | 96.51 | Average | 97.25 | 97.25 | 97.14 | 97.19 | 97.28 |
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