Name
Title | ||
|---|---|---|
Attention-based deep residual learning network for entity relation extraction in Chinese EMRs. |
Abstract | ||
|---|---|---|
The residual network-based model can reduce the negative impact of corpus noise to parameter learning, and the combination of character position attention mechanism will enhance the identification features of different type of entities. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1186/s12911-019-0769-0 | BMC Med. Inf. & Decision Making |
Keywords | Field | DocType |
Attention mechanism,Chinese electronic medical record,Deep residual learning network,Entity relation extraction | Data mining,Residual,Information retrieval,Parameter learning,Information extraction,Automatic processing,Health informatics,Residual neural network,Medicine,Learning network,Relationship extraction | Journal |
Volume | Issue | ISSN |
19-S | 2 | 1472-6947 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhichang Zhang | 1 | 1 | 2.39 |
| Tong Zhou | 2 | 448 | 76.83 |
| Yu Zhang | 3 | 188 | 31.14 |
| Yali Pang | 4 | 0 | 0.34 |