Meeting medical terminology needs - The ontology-enhanced Medical Concept Mapper

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56 Scopus citations

Abstract

This paper describes the development and testing of the Medical Concept Mapper, a tool designed to facilitate access to online medical information sources by providing users with appropriate medical search terms for their personal queries. Our system is valuable for patients whose knowledge of medical vocabularies is inadequate to find the desired information, and for medical experts who search for information outside their field of expertise. The Medical Concept Mapper maps synonyms and semantically related concepts to a user's query The system is unique because it integrates our natural language processing tool, i.e., the Arizona (AZ) Noun Phraser, with human-created ontologies, the Unified Medical Language System (UMLS) and WordNet, and our computer generated Concept Space, into one system. Our unique contribution results from combining the UMLS Semantic Net with Concept Space in our deep semantic parsing (DSP) algorithm. This algorithm establishes a medical query context based on the UMLS Semantic Net, which allows Concept Space terms to be filtered so as to isolate related terms relevant to the query. We performed two user studies in which Medical Concept Mapper terms were compared against human experts' terms. We conclude that the AZ Noun Phraser is well suited to extract medical phrases from user queries, that WordNet is not well suited to provide strictly medical synonyms, that the UMLS Metathesaurus is well suited to provide medical synonyms, and that Concept Space is well suited to provide related medical terms, especially when these terms are limited by our DSP algorithm.

Original languageEnglish (US)
Pages (from-to)261-270
Number of pages10
JournalIEEE Transactions on Information Technology in Biomedicine
Volume5
Issue number4
DOIs
StatePublished - Dec 2001

Keywords

  • Ontologies
  • Parsing
  • Query expansion
  • Semantic parsing
  • Terminology mapping
  • UMLS

ASJC Scopus subject areas

  • Biotechnology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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