Pooling annotated corpora for clinical concept extraction.

ABSTRACT:

Background

The availability of annotated corpora has facilitated the application of machine learning algorithms to concept extraction from clinical notes. However, high expenditure and labor are required for creating the annotations. A potential alternative is to reuse existing corpora from other institutions by pooling with local corpora, for training machine taggers. In this paper we have investigated the latter approach by pooling corpora from 2010 i2b2/VA NLP challenge and Mayo Clinic Rochester, to evaluate taggers for recognition of medical problems. The corpora were annotated for medical problems, but with different guidelines. The taggers were constructed using an existing tagging system MedTagger that consisted of dictionary lookup, part of speech (POS) tagging and machine

SUBMITTER: Wagholikar KB 

PROVIDER: S-EPMC3599895 | biostudies-literature | 2013 Jan

REPOSITORIES: biostudies-literature