Name
Title | ||
|---|---|---|
Semi-Supervised Recurrent Neural Network for Adverse Drug Reaction Mention Extraction. |
Abstract | ||
|---|---|---|
In this study, we tackle the problem of labeled data scarcity for Adverse Drug Reaction mention extraction from social media and propose a novel semi-supervised learning based method which can leverage large unlabeled corpus available in abundance on the web. Through empirical study, we demonstrate that our proposed method outperforms fully supervised learning based baseline which relies on large manually annotated corpus for a good performance. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1186/s12859-018-2192-4 | BMC Bioinformatics |
Keywords | DocType | Volume |
Pharmacovigilance,Recurrent neural networks,Semi-supervised learning | Journal | abs/1709.01687 |
Issue | ISSN | Citations |
8 | 1471-2105 | 2 |
PageRank | References | Authors |
0.38 | 14 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| shashank gupta | 1 | 60 | 11.35 |
| Sachin Pawar | 2 | 14 | 8.42 |
| Nitin Ramrakhiyani | 3 | 7 | 5.67 |
| Girish Keshav Palshikar | 4 | 126 | 25.59 |
| Vasudeva Varma | 5 | 640 | 95.84 |