Anatomical entity mention recognition at literature scale.

ABSTRACT:

Motivation

Anatomical entities ranging from subcellular structures to organ systems are central to biomedical science, and mentions of these entities are essential to understanding the scientific literature. Despite extensive efforts to automatically analyze various aspects of biomedical text, there have been only few studies focusing on anatomical entities, and no dedicated methods for learning to automatically recognize anatomical entity mentions in free-form text have been introduced.

Results

We present AnatomyTagger, a machine learning-based system for anatomical entity mention recognition. The system incorporates a broad array of approaches proposed to benefit tagging, including the use of Unified Medical Language System (UMLS)- and Open Biomedical Ontologies (OBO)-base

SUBMITTER: Pyysalo S 

PROVIDER: S-EPMC3957068 | biostudies-literature | 2014 Mar

REPOSITORIES: biostudies-literature