Literature DB >> 29854199

Distinction between medical and non-medical usages of short forms in clinical narratives.

Sungrim Moon1, Donna Ihrke1, Yuqun Zeng1, Hongfang Liu1.   

Abstract

The short forms of medical concepts or expressions (i.e., acronyms/abbreviations) are prevalent in clinical documentation. Given the limited number of potential short forms, they are also highly ambiguous. Resolving the ambiguity of short forms is essential in clinical natural language processing (NLP). However, one prerequisite for resolving ambiguity of short forms is to have a sense inventory. This paper outlines our process of identifying 141 potential short forms with randomly sampled phrases from a large clinical corpus. We assessed various features in their ability to disambiguate medical and non-medical usages. We identified 68% of our short forms as primarily serving medical usages, whereas 12% had non-medical usages. The remaining 19% showed alternating usage based upon case form. Our short forms had an average of 3.58 senses. Usages could be distinguished using basic trigram/bigram/line information. Our initial findings will be applicable for automatic usage/sense resolution.

Mesh:

Year:  2018        PMID: 29854199      PMCID: PMC5977717     

Source DB:  PubMed          Journal:  AMIA Annu Symp Proc        ISSN: 1559-4076


  9 in total

1.  A study of abbreviations in the UMLS.

Authors:  H Liu; Y A Lussier; C Friedman
Journal:  Proc AMIA Symp       Date:  2001

2.  The sublanguage of cross-coverage.

Authors:  Peter D Stetson; Stephen B Johnson; Matthew Scotch; George Hripcsak
Journal:  Proc AMIA Symp       Date:  2002

3.  Abbreviation and acronym disambiguation in clinical discourse.

Authors:  Sergeui Pakhomov; Ted Pedersen; Christopher G Chute
Journal:  AMIA Annu Symp Proc       Date:  2005

4.  A comparative study of supervised learning as applied to acronym expansion in clinical reports.

Authors:  Mahesh Joshi; Serguei Pakhomov; Ted Pedersen; Christopher G Chute
Journal:  AMIA Annu Symp Proc       Date:  2006

5.  Methods for building sense inventories of abbreviations in clinical notes.

Authors:  Hua Xu; Peter D Stetson; Carol Friedman
Journal:  J Am Med Inform Assoc       Date:  2008-10-24       Impact factor: 4.497

6.  A sense inventory for clinical abbreviations and acronyms created using clinical notes and medical dictionary resources.

Authors:  Sungrim Moon; Serguei Pakhomov; Nathan Liu; James O Ryan; Genevieve B Melton
Journal:  J Am Med Inform Assoc       Date:  2013-06-27       Impact factor: 4.497

7.  Automated disambiguation of acronyms and abbreviations in clinical texts: window and training size considerations.

Authors:  Sungrim Moon; Serguei Pakhomov; Genevieve B Melton
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

8.  Combining corpus-derived sense profiles with estimated frequency information to disambiguate clinical abbreviations.

Authors:  Hua Xu; Peter D Stetson; Carol Friedman
Journal:  AMIA Annu Symp Proc       Date:  2012-11-03

9.  Word sense disambiguation in the clinical domain: a comparison of knowledge-rich and knowledge-poor unsupervised methods.

Authors:  Rachel Chasin; Anna Rumshisky; Ozlem Uzuner; Peter Szolovits
Journal:  J Am Med Inform Assoc       Date:  2014-01-17       Impact factor: 4.497

  9 in total

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