Improving Terminology Mapping in Clinical Text with Context-Sensitive Spelling Correction.

Journal: Studies in health technology and informatics
Published Date:

Abstract

The mapping of unstructured clinical text to an ontology facilitates meaningful secondary use of health records but is non-trivial due to lexical variation and the abundance of misspellings in hurriedly produced notes. Here, we apply several spelling correction methods to Swedish medical text and evaluate their impact on SNOMED CT mapping; first in a controlled evaluation using medical literature text with induced errors, followed by a partial evaluation on clinical notes. It is shown that the best-performing method is context-sensitive, taking into account trigram frequencies and utilizing a corpus-based dictionary.

Authors

  • Juliusz Dziadek
    Department of Computer and Systems Sciences, Stockholm University.
  • Aron Henriksson
  • Martin Duneld
    Department of Computer and Systems Sciences, Stockholm University.