Taxonomy Learning from Health Care Social Communities to Improve EHR Implementation | Zendy

Zahia Marouf | Zendy; Sidi Mohamed Benslimane | Zendy

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Taxonomy Learning from Health Care Social Communities to Improve EHR Implementation

Author(s) -

Zahia Marouf,

Sidi Mohamed Benslimane

Publication year - 2018

Publication title -

international journal of modern education and computer science

Language(s) - English

Resource type - Journals

eISSN - 2075-017X

pISSN - 2075-0161

DOI - 10.5815/ijmecs.2018.06.06

Subject(s) - leverage (statistics) , computer science , exploit , economic shortage , electronic health record , complement (music) , microdata (statistics) , health care , taxonomy (biology) , semantics (computer science) , health records , data science , social care , knowledge management , world wide web , artificial intelligence , computer security , nursing , medicine , programming language , economic growth , biology , economics , population , philosophy , government (linguistics) , linguistics , chemistry , environmental health , census , biochemistry , botany , complementation , gene , phenotype

In this paper, we propose an approach to extract ontological structures from datasets generated by health care users of social networking sites. The objective of this approach is to exploit the user generated implicit semantics as a complement to more formalized knowledge representations. We aim for this latter to leverage the adoption level of the Electronic Health Record systems that are complaining from the shortage in standards and controlled vocabularies.

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