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        <title>WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts</title>
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        <namePart type="given">Sivaji</namePart>
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    <abstract>Information extraction in the medical domain is laborious and time-consuming due to the insufficient number of domain-specific lexicons and lack of involvement of domain experts such as doctors and medical practitioners. Thus, in the present work, we are motivated to design a new lexicon, WME 3.0 (WordNet of Medical Events), which contains over 10,000 medical concepts along with their part of speech, gloss (descriptive explanations), polarity score, sentiment, similar sentiment words, category, affinity score and gravity score features. In addition, the manual annotators help to validate the overall as well as individual category level of medical concepts of WME 3.0 using Cohen’s Kappa agreement metric. The agreement score indicates almost correct identification of medical concepts and their assigned features in WME 3.0.</abstract>
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%0 Conference Proceedings
%T WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts
%A Mondal, Anupam
%A Das, Dipankar
%A Cambria, Erik
%A Bandyopadhyay, Sivaji
%Y Bond, Francis
%Y Vossen, Piek
%Y Fellbaum, Christiane
%S Proceedings of the 9th Global Wordnet Conference
%D 2018
%8 January
%I Global Wordnet Association
%C Nanyang Technological University (NTU), Singapore
%F mondal-etal-2018-wme
%X Information extraction in the medical domain is laborious and time-consuming due to the insufficient number of domain-specific lexicons and lack of involvement of domain experts such as doctors and medical practitioners. Thus, in the present work, we are motivated to design a new lexicon, WME 3.0 (WordNet of Medical Events), which contains over 10,000 medical concepts along with their part of speech, gloss (descriptive explanations), polarity score, sentiment, similar sentiment words, category, affinity score and gravity score features. In addition, the manual annotators help to validate the overall as well as individual category level of medical concepts of WME 3.0 using Cohen’s Kappa agreement metric. The agreement score indicates almost correct identification of medical concepts and their assigned features in WME 3.0.
%U https://aclanthology.org/2018.gwc-1.2
%P 10-16

Markdown (Informal)

[WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts](https://aclanthology.org/2018.gwc-1.2) (Mondal et al., GWC 2018)

• WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts (Mondal et al., GWC 2018)

ACL

• Anupam Mondal, Dipankar Das, Erik Cambria, and Sivaji Bandyopadhyay. 2018. WME 3.0: An Enhanced and Validated Lexicon of Medical Concepts. In Proceedings of the 9th Global Wordnet Conference, pages 10–16, Nanyang Technological University (NTU), Singapore. Global Wordnet Association.