Medical event coreference resolution using the UMLS metathesaurus and temporal reasoning

  • Authors:
  • Preethi Raghavan;Eric Fosler-Lussier;Chris Brew;Albert M. Lai

  • Affiliations:
  • The Ohio State University, Columbus, OH, USA;The Ohio State University, Columbus, OH, USA;Educational Testing Service, Princeton, NJ, USA;The Ohio State University, Columbus, OH, USA

  • Venue:
  • Proceedings of the 2nd ACM SIGHIT International Health Informatics Symposium
  • Year:
  • 2012

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Abstract

We study the problem of medical event coreference resolution in clinical text. Clinical text found in clinical narratives and patient case reports usually reflects a sublanguage with medicine specific terminology. It is also frequently characterized by temporal expressions co-occurring with medical events. In this paper, we outline a method for quantifying the similarity between medical events found in the New England Journal of Medicine patient case reports. We believe this method will be valuable in classifying medical events as coreferential. We approach this problem by determining the overlap between pairs of medical events in terms of 1) the relation between medical events in the UMLS graph structure and 2) the temporal relation between the medical events. We demonstrate our ideas on a corpus of New England Journal of Medicine case reports annotated with coreference information. Preliminary results indicate a precision of 78.5% and recall of 95.5% in identifying pairs of coreferential medical events.