Table 6.

Results for concept recognition experiments on 1800 Multiparameter Intelligent Monitoring in Intensive Care documents. The Neural Concept Recognizer models were trained on a subset of the Systematized Nomenclature of Medicine - Clinical Terms ontology. Largest values for each category are italicized.

Method	Micro (%)			Macro (%)
	Precision	Recall	F1-score	Precision	Recall	F1-score
cTAKESa	9.1	37.0	14.6	8.7	36.5	14.1
NCRb	10.9	26.7	15.5	10.6	26.9	15.2
NCR-Hc	10.0	30.6	15.1	9.6	30.4	14.6
NCR-Nd	11.2	24.8	15.4	11.1	25.3	15.4
NCR-HNe	9.6	28.6	14.4	9.2	28.9	13.9

^acTAKES: Clinical Text Analysis and Knowledge Extraction System.

^bNCR: Neural Concept Recognizer.

^cNCR-H: variation of the NCR model that ignores taxonomic relations.

^dNCR-N: variation of the NCR model that has not been trained on negative samples.

^eNCR-HN: variation of the NCR model that ignores the taxonomy and has not been trained on negative examples.