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Abbreviation and Acronym Identification and Expansion Within Medical Health Records

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Author(s)
Wallace, Duncan 
Kechadi, Tahar 
Uri
http://hdl.handle.net/10197/9937
Date Issued
22 July 2017
Date Available
15T08:27:51Z April 2019
Abstract
Recent years have seen the rapid increase in digitised medical information. In particular, the massive expansion of Electronic Health Records (EHRs), which are designed to document all information that is clinically relevant in a patient's use of a healthcare facility, has introduced unprecedented volumes of relatively unstructured data. This paper intends to determine the extent to which knowledge discovery in relation to both abbreviations and acronyms within heterogeneous data can be achieved. Heterogeneous data such as the narrative-based free-text notes found within patients' EHRs may use inconsistent ways to indicate contractions within the text and may use non-standard definitions for both abbreviations and acronyms. We approached this task through the retrieval and classification of contractions as well as using a novel method of combining multiple publically available repositories. In order to provide better coverage of abbreviations, and also to address the issue of neologisms in general, word embeddings were applied to find semantically similar lexemes.
Sponsorship
Science Foundation Ireland
Other Sponsorship
Carlow Emergency Doctors On Call – CAREDOC
Type of Material
Conference Publication
Publisher
IADIS
Start Page
102
End Page
108
Copyright (Published Version)
2017 the Authors
Keywords
  • Bio-informatics

  • Text-mining

  • Natural language proc...

  • Feature selection

Language
English
Status of Item
Peer reviewed
Description
The 9th International Conference on e-Health, Lisbon, Portugal, 20-22 July 2017
ISBN
978-989-8533-65-4
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Insight Research Collection
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