Name
Title | ||
|---|---|---|
A two-stage deep learning approach for extracting entities and relationships from medical texts. |
Abstract | ||
|---|---|---|
•A new two-stage deep learning approach for information extraction from medical texts.•Hybrid model using Bi-LSTM, CRF and CNN.•State-of-the-art results on the eHealth-KD dataset and DDI dataset for NER.•First two-stage information extraction system for Drug-Drug Interactions from texts. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jbi.2019.103285 | Journal of Biomedical Informatics |
Keywords | Field | DocType |
Name entity recognition,Relation extraction,Deep learning,Health documents | Conditional random field,Ontology (information science),Text simplification,Information retrieval,Computer science,Natural language understanding,Biomedical text mining,Artificial intelligence,Deep learning,Named-entity recognition,Relationship extraction | Journal |
Volume | ISSN | Citations |
99 | 1532-0464 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Víctor Suárez-Paniagua | 1 | 4 | 1.84 |
| Renzo M Rivera Zavala | 2 | 0 | 0.34 |
| Isabel Segura-Bedmar | 3 | 435 | 30.96 |
| Paloma Martínez | 4 | 717 | 85.63 |