Named Entity Recognition in Portuguese Neurology Text Using CRF

Abstract

Automatic recognition of named entities from clinical text lightens the work of health professionals by helping in the interpretation and easing tasks such as the population of databases with patient health information. In this study, we evaluated the performance of Conditional Random Fields, a sequence labelling model, for extracting entities from neurology clinical texts written in Portuguese. More than achieving F1-scores of about 73% or 80%, respectively for a relaxed or strict evaluation, the more discriminant features in this task were also analyzed.