Table 2:
Performance Comparison of Extant Systems
| BC5CDR (d) | BC5CDR (c) | CADEC | NCBI Disease | n2c2 2019 | ShARe/CLEF | |
|---|---|---|---|---|---|---|
| Chen, et al. [70] | - | - | - | - | 82.1 | - |
| D’Souza, et al. [16] | - | - | - | 84.7 | - | 90.8 |
| Ji, et al. [71] | - | - | - | 89.1 | - | 91.1 |
| Lee, et al. [72] | - | - | 65.0 | - | - | - |
| Li, et al. [73] | - | - | - | 86.1 | - | 90.3 |
| Liu, et al. (SAPBERT) [30] | 93.5 | 96.5 | - | 92.3 | - | - |
| Limsopatham and Collier [63] | - | - | 81.41 | - | - | - |
| Kalyan, et al. [74] | - | - | 82.6 | - | - | - |
| Miftahutdinov and Tutubalina (2018) [67] | - | - | 88.8 | - | - | - |
| Miftahutdinov, et al. (2021) [75] | 75.8 | 83.8 | - | - | - | - |
| Mondal, et al. [76] | - | - | - | 90.0 | - | - |
| Niu, et al. [26] | - | - | 84.7 | - | - | - |
| Pattisapu, et al. [77] | - | - | 76.7 | - | - | - |
| Phan, et al. [78] | 90.6 | 95.8 | - | 87.7 | - | - |
| Schumacher, et al. [68] | - | - | - | - | - | 62 |
| Silva, et al. [79] | - | - | - | - | 80.6 | - |
| Sung, et al. [29] | 93.2 | 96.6 | - | 91.1 | - | - |
| Tutubalina, et al. (2018) [25] | - | - | 70.1 | - | - | - |
| Wright, et al. [80] | 88 | - | - | 87.8 | - | - |
| Xu, et al. (2020) [81] | - | - | 87.5 | - | 83.6 | - |
| Xu and Miller (2022) [82] | - | - | - | - | 85.3 | 91.3 |
| Zhang, et al. (KRISSBERT) [69] | 90.7 | 96.9 | - | 89.9 | 80.2 | 90.4 |
| Zhao, et al. [83] | - | - | - | 88.2 | - | - |
Comparison of reported accuracies on six popular BEL datasets. The BC5CDR dataset contains partitions corresponding to disease (d) and chemical (c) normalization, which are often evaluated separately.