Table 2 Performances of single-task models
From: CollaboNet: collaboration of deep neural networks for biomedical named entity recognition
Model | Habibi et al. (2017) STM | Wang et al. (2018) STM | Our STM | ||||||
|---|---|---|---|---|---|---|---|---|---|
Dataset | Precision | Recall | F1 Score | Precision | Recall | F1 Score | Precision | Recall | F1 Score |
NCBI-disease | 85.31 | 83.58 | 84.44 | 84.95 | 82.92 | 83.92 | 83.95 | 85.45 | 84.69 (±0.54) |
JNLPBA | 74.83 | 79.82 | 77.25 | 69.60 | 74.95 | 72.17 | 72.51 | 82.98 | 77.39 (±0.24) |
BC5CDR-chem | 92.57 | 88.77 | 90.63 | *93.05 | *86.87 | *89.85 | 94.02 | 91.50 | 92.74 (±0.47) |
BC5CDR-disease | 84.19 | 82.79 | 83.49 | *84.09 | *81.32 | *82.68 | 82.98 | 82.25 | 82.61 (±0.25) |
BC4CHEMD | 87.83 | 85.45 | 86.62 | 90.53 | 87.04 | 88.75 | 90.50 | 85.96 | 88.19 (±0.23) |
BC2GM | 77.50 | 78.13 | 77.82 | 81.11 | 78.91 | 80.00 | 79.70 | 77.47 | 78.56 (±0.38) |
Macro Average | 83.71 | 83.09 | 83.38 | 83.89 | 82.00 | 82.90 | 83.94 | 84.27 | 84.03 |