Representing Clinical Diagnostic Criteria in Quality Data Model Using Natural Language Processing

Na Hong, Dingcheng Li, Yue Yu, Hongfang Liu, Christopher G. Chute, Guoqian Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Constructing standard and computable clinical diagnostic criteria is an important and challenging research area in clinical informatics community. In this study, we present our framework and methods for representing clinical diagnostic criteria in Quality Data Model (QDM) using natural language processing (NLP) technologies. We used a clinical NLP tool known as cTAKES for preprocessing of textual diagnostic criteria. We created mappings between cTAKES type system and QDM elements in both datatype and data levels. We evaluated the performance of our NLP-based approach by annotating 218 individual diagnostic criteria in the categories of Symptom and Laboratory Test. In conclusion, our NLP-based approach is a feasible solution in developing diagnostic criteria representation and computerization.

Original languageEnglish (US)
Title of host publicationACL-IJCNLP 2015 - BioNLP 2015
Subtitle of host publicationWorkshop on Biomedical Natural Language Processing, Proceedings of the Workshop
PublisherAssociation for Computational Linguistics (ACL)
Pages177-182
Number of pages6
ISBN (Electronic)1932432663, 9781932432664
StatePublished - 2015
EventACL-IJCNLP 2015 Workshop on Biomedical Natural Language Processing, BioNLP 2015 - Beijing, China
Duration: Jul 30 2015 → …

Publication series

NameACL-IJCNLP 2015 - BioNLP 2015: Workshop on Biomedical Natural Language Processing, Proceedings of the Workshop

Conference

ConferenceACL-IJCNLP 2015 Workshop on Biomedical Natural Language Processing, BioNLP 2015
Country/TerritoryChina
CityBeijing
Period7/30/15 → …

ASJC Scopus subject areas

  • Health Informatics
  • Language and Linguistics
  • Computer Science Applications
  • Information Systems
  • Software
  • Biomedical Engineering

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