Table 4.
Extended measurements for concept recognition experiments on 188 PubMed abstracts. Neural Concept Recognizer models were trained on Human Phenotype Ontology. Largest values for each category are italicized.
| Method | Extended value (%) | Jaccard value (%) | ||
|
|
Precision | Recall | F1-score | |
| BioLarK | 91.5 | 80.8 | 85.8 | 76.9 |
| cTAKESa | 95.6 | 73.9 | 83.3 | 72.1 |
| OBOb | 92.4 | 77.9 | 84.5 | 74.4 |
| NCBOc | 95.8 | 65.4 | 77.7 | 64.3 |
| NCRd | 93.3 | 82.1 | 87.3 | 79.1 |
| NCR-He | 86.5 | 83.8 | 85.1 | 76.7 |
| NCR-Nf | 90.6 | 83.1 | 86.7 | 78.2 |
| NCR-HNg | 89.7 | 78.9 | 83.9 | 73.2 |
acTAKES: Clinical Text Analysis and Knowledge Extraction System.
bOBO: Open Biological and Biomedical Ontologies
cNCBO: National Center for Biomedical Ontology.
dNCR: Neural Concept Recognizer.
eNCR-H: variation of the NCR model that ignores taxonomic relations.
fNCR-N: variation of the NCR model that has not been trained on negative samples.
gNCR-HN: variation of the NCR model that ignores the taxonomy and has not been trained on negative examples.