Name
Title | ||
|---|---|---|
Extracting COVID-19 diagnoses and symptoms from clinical text: A new annotated corpus and neural event extraction framework |
Abstract | ||
|---|---|---|
•We present a corpus with annotations for COVID-19 diagnoses, testing, and symptoms.•A detailed event-based symptom annotation scheme is introduced.•Our neural extractor achieves high performance for symptom and assertion prediction.•The symptomology of COVID-19 is explored through a COVID-19 prediction application. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jbi.2021.103761 | Journal of Biomedical Informatics |
Keywords | DocType | Volume |
COVID-19,Coronavirus,Machine learning,Natural language processing,Information extraction | Journal | 117 |
ISSN | Citations | PageRank |
1532-0464 | 1 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kevin Lybarger | 1 | 4 | 1.42 |
| Mari Ostendorf | 2 | 2462 | 348.75 |
| Matthew Thompson | 3 | 15 | 3.95 |
| Meliha Yetisgen-Yildiz | 4 | 328 | 34.25 |