Use abstracted patient-specific features to assist an information-theoretic measurement to assess similarity between medical cases

Hui Cao, Genevieve B. Melton, Marianthi Markatou, George Hripcsak

Research output: Contribution to journalArticle

21 Scopus citations

Abstract

Inter-case similarity metrics can potentially help find similar cases from a case base for evidence-based practice. While several methods to measure similarity between cases have been proposed, developing an effective means for measuring patient case similarity remains a challenging problem. We were interested in examining how abstracting could potentially assist computing case similarity. In this study, abstracted patient-specific features from medical records were used to improve an existing information-theoretic measurement. The developed metric, using a combination of abstracted disease, finding, procedure and medication features, achieved a correlation between 0.6012 and 0.6940 to experts.

Original languageEnglish (US)
Pages (from-to)882-888
Number of pages7
JournalJournal of Biomedical Informatics
Volume41
Issue number6
DOIs
StatePublished - Dec 1 2008

Keywords

  • Abstracting
  • Case similarity
  • Case-based reasoning
  • Patient feature

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