Research Article
Medical Text Classification Using Hybrid Deep Learning Models with Multihead Attention
Table 13
Analysis of results with different activation functions for the proposed hybrid BiGRU model.
| Optimizer | Dataset | Accuracy (%) | Precision (%) | Recall (%) | F1-score (%) |
| ReLU | Hallmarks | 71.64 | 67.39 | 66.69 | 67.03 | AIM | 88.39 | 82.20 | 83.61 | 82.89 |
| Sigmoid | Hallmarks | 74.69 | 72.29 | 71.91 | 72.09 | AIM | 94.29 | 89.74 | 88.56 | 89.14 |
| SoftPlus | Hallmarks | 73.12 | 71.03 | 71.82 | 71.42 | AIM | 83.39 | 81.91 | 82.84 | 82.37 |
| Hard sigmoid | Hallmarks | 61.22 | 58.92 | 57.41 | 58.15 | AIM | 85.87 | 83.19 | 81.49 | 82.33 |
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