Table 2.
Performance values in terms of the precision (%), recall (%) and F1-score (%) for the state-of-the-art methods and the proposed model DTranNER
| Corpus | BC2GM | BC4CHEMD | BC5CDR-Chemical | BC5CDR-Disease | NCBI-Disease | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| P | R | F1 | P | R | F1 | P | R | F1 | P | R | F1 | P | R | F1 | |
| Att-BiLSTM-CRF (2017) | - | - | - | 92.29 | 90.01 | 91.14 | 93.49 | 91.68 | 92.57 | - | - | - | - | - | - |
| D3NER (2018) | - | - | - | - | - | - | 93.73 | 92.56 | 93.14 | 83.98 | 85.40 | 84.68 | 85.03 | 83.80 | 84.41 |
| Collabonet (2018) | 80.49 | 78.99 | 79.73 | 90.78 | 87.01 | 88.85 | 94.26 | 92.38 | 93.31 | 85.61 | 82.61 | 84.08 | 85.48 | 87.27 | 86.36 |
| Wang et al. (2018) | 82.10 | 79.42 | 80.74 | 91.30 | 87.53 | 89.37 | 93.56 | 92.48 | 93.03 | 84.14 | 85.76 | 84.95 | 85.86 | 86.42 | 86.14 |
| BioBERT (2019) | 85.16 | 83.65 | 84.40 | 92.23 | 90.61 | 91.41 | 93.27 | 93.61 | 93.44 | 85.86 | 87.27 | 86.56 | 89.04 | 89.69 | 89.36 |
| DTranNER | 84.21 | 84.84 | 84.56 | 91.94 | 92.04 | 91.99 | 94.28 | 94.04 | 94.16 | 86.75 | 87.70 | 87.22 | 88.21 | 89.04 | 88.62 |
Note: The highest performance in each corpus is highlighted in Bold. We quoted the published scores for the other models. For Wang et al. [11], we conducted additional experiments to obtain the performance scores for two corpora (i.e., BC5CDR-Chemical and BC5CDR-Disease) using the software on their open source repository [45]