HTNSystem: Hypertension information extraction system for unstructured clinical notes

Jitendra Jonnagaddala, Siaw Teng Liaw, Pradeep Ray, Manish Kumar, Hong Jie Dai

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Hypertension (HTN) relevant information has great application potential in cohort discovery and building predictive models for prevention and surveillance. Unfortunately most of this valuable patient information is buried in the form of unstructured clinical notes. In this study we present HTN information extraction system called HTNSystem which is capable of extracting mentions of HTN and inferring HTN from BP lab values. HTNSystem is a rule based system which implements MetaMap as a core component together with custom built BP value extractor and post processing components. It is evaluated on a corpus of 514 clinical notes (82.92% F-measure). HTNSystem is distributed as an open source command line tool available at https://github.com/TCRNBioinformatics/HTNSystem.

Original languageEnglish
Pages (from-to)219-227
Number of pages9
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8916
Publication statusPublished - 2014

Keywords

  • Apache Ruta
  • Apache UIMA
  • Blood pressure
  • Hypertension
  • Information extraction
  • Rule based
  • Text mining

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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