PMC:7782580 / 945-1399
Annnotations
LitCovid-PubTator
Id | Subject | Object | Predicate | Lexical cue | tao:has_database_id |
---|---|---|---|---|---|
11 | 188-196 | Disease | denotes | COVID-19 | MESH:C000657245 |
17 | 321-329 | Disease | denotes | COVID-19 | MESH:C000657245 |
18 | 330-339 | Disease | denotes | infection | MESH:D007239 |
19 | 415-443 | Disease | denotes | upper respiratory infections | MESH:D012141 |
LitCovid-PD-HP
Id | Subject | Object | Predicate | Lexical cue | hp_id |
---|---|---|---|---|---|
T1 | 421-443 | Phenotype | denotes | respiratory infections | http://purl.obolibrary.org/obo/HP_0011947 |
LitCovid-sentences
Id | Subject | Object | Predicate | Lexical cue |
---|---|---|---|---|
T9 | 109-218 | Sentence | denotes | The proposed method represents a potential computer-aided diagnosis method for COVID-19 in clinical practice. |
T10 | 220-444 | Sentence | denotes | Liang, Gu and other colleagues develop a convoluted neural network (CNN)-based framework to diagnose COVID-19 infection from chest X-ray and computed tomography images, and comparison with other upper respiratory infections. |