Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters.

ABSTRACT:

Background

Ontological concepts are useful for many different biomedical tasks. Concepts are difficult to recognize in text due to a disconnect between what is captured in an ontology and how the concepts are expressed in text. There are many recognizers for specific ontologies, but a general approach for concept recognition is an open problem.

Results

Three dictionary-based systems (MetaMap, NCBO Annotator, and ConceptMapper) are evaluated on eight biomedical ontologies in the Colorado Richly Annotated Full-Text (CRAFT) Corpus. Over 1,000 parameter combinations are examined, and best-performing parameters for each system-ontology pair are presented.

Conclusions

Baselines for concept recognition by three systems on eight biomedical ontologies are established (F-measur

SUBMITTER: Funk C 

PROVIDER: S-EPMC4015610 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature