<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>

COPY SCRIPT

For further information contact us at helpdesk@openaire.eu

Wikidata: A large-scale collaborative ontological medical database

descriptionPublicationkeyboard_double_arrow_right Article , Other literature type 01 Nov 2019 English Publisher:Elsevier BVJournal:Journal of Biomedical Informatics, volume 99, page 103,292 (issn: 1532-0464,

Authors: Houcemeddine Turki; Thomas Shafee; Mohamed Ali Hadj Taieb; Mohamed Ben Aouicha; Denny Vrandečić; Diptanshu Das; Helmi Hamdi;

doi: 10.1016/j.jbi.2019.103292 , 10.26181/25441165 , 10.26181/25441165.v1

pmid: 31557529

Wikidata: A large-scale collaborative ontological medical database

- Summary
- Subjects
- Metrics

Abstract

No description supplied.

Related Organizations

La Trobe University
Australia
Université de Sherbrooke
Canada
Google (United States)
United States
University of Sfax
Tunisia
Institute of Neurosciences Kolkata
India

Keywords

Internet, Artificial intelligence, Databases, Factual, Data management and data science, Applied computing, Multilingualism, Semantics, Biological Ontologies, Health services and systems, Information and computing sciences, Database Management Systems, Electronic Health Records, Humans

Impact byBIP!

	citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	34
	popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.	Top 10%
	influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).	Top 10%
	impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.	Top 10%