Ontology-based clinical information extraction from physician's free-text notes

J Biomed Inform. 2019 Oct:98:103276. doi: 10.1016/j.jbi.2019.103276. Epub 2019 Aug 29.

Abstract

Documenting clinical notes in electronic health records might affect physician's workflow. In this paper, an Ontology-based clinical information extraction system, OB-CIE, has been developed. OB-CIE system provides a method for extracting clinical concepts from physician's free-text notes and converts the unstructured clinical notes to structured information to be accessed in electronic health records. OB-CIE system can help physicians to document visit notes without changing their workflow. For recognizing named entities of clinical concepts, ontology concepts have been used to construct a dictionary of semantic categories, then, exact dictionary matching method has been used to match noun phrases to their semantic categories. A rule-based approach has been used to classify clinical sentences to their predefined categories. The system evaluation results have achieved an F-measure of 94.90% and 97.80% for concepts classification and sentences classification, respectively. The results have showed that OB-CIE system performed well on extracting clinical concepts compared with data mining techniques. The system can be used in another field by adapting its ontology and extraction rule set.

Keywords: Electronic health records; Information extraction; Natural language processing.

MeSH terms

  • Data Mining / methods*
  • Electronic Health Records*
  • Humans
  • Information Storage and Retrieval / methods
  • Machine Learning
  • Medical Informatics / methods*
  • Natural Language Processing
  • Pattern Recognition, Automated
  • PubMed
  • Reproducibility of Results
  • Semantics