研究文章
药物警戒与变形金刚:一个框架来检测药品不良反应使用伯特微调和农场
表6
比较的结果成果通过FARM-BERT TwiMed语料库取得了最先进的模型。
|
| 模型 |
TwiMed-Twitter |
TwiMed-PubMed |
|
|
|
|
|
|
|
|
| 支持向量机(48] |
0.752 |
0.810 |
0.778 |
0.799 |
0.681 |
0.728 |
| 伊恩(48] |
0.836 |
0.813 |
0.824 |
0.878 |
0.738 |
0.792 |
| CNN-based方法(49] |
0.739 |
0.788 |
0.761 |
0.849 |
0.831 |
0.835 |
| 多通道CNN (50] |
0.738 |
0.841 |
0.780 |
0.861 |
0.780 |
0.816 |
| 联合AB-LSTM [51] |
0.748 |
0.856 |
0.799 |
0.858 |
0.852 |
0.853 |
| MSAM [47] |
0.701 |
0.828 |
0.754 |
0.817 |
0.856 |
0.831 |
| FARM-BERT |
0.831 |
0.868 |
0.849 |
0.952 |
0.966 |
0.959 |
|
|
