A novel query rewriting mechanism for semantically interlinking clinical research with electronic health records

Chondrogiannis, E; Andronikou, V; Mourtzoukos, K; Tagaris, A; Varvarigou, T

dc.contributor.author	Chondrogiannis, E	en
dc.contributor.author	Andronikou, V	en
dc.contributor.author	Mourtzoukos, K	en
dc.contributor.author	Tagaris, A	en
dc.contributor.author	Varvarigou, T	en
dc.date.accessioned	2014-03-01T02:53:32Z
dc.date.available	2014-03-01T02:53:32Z
dc.date.issued	2012	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36400
dc.subject	Bioinformatics	en
dc.subject	Ontology alignment	en
dc.subject	Query transformation	en
dc.subject.other	Automatic selection	en
dc.subject.other	Clinical research	en
dc.subject.other	Clinical trial	en
dc.subject.other	Data sets	en
dc.subject.other	Different domains	en
dc.subject.other	Electronic health record	en
dc.subject.other	Emerging trends	en
dc.subject.other	Heterogeneous database	en
dc.subject.other	Ontology alignment	en
dc.subject.other	Ontology-based	en
dc.subject.other	Query rewritings	en
dc.subject.other	Query transformations	en
dc.subject.other	Secondary use	en
dc.subject.other	Bioinformatics	en
dc.subject.other	Experiments	en
dc.subject.other	Patient treatment	en
dc.subject.other	Records management	en
dc.subject.other	Semantics	en
dc.subject.other	Semantic Web	en
dc.title	A novel query rewriting mechanism for semantically interlinking clinical research with electronic health records	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/2254129.2254189	en
heal.identifier.secondary	http://dx.doi.org/10.1145/2254129.2254189	en
heal.identifier.secondary	48	en
heal.publicationDate	2012	en
heal.abstract	Electronic Health Records (EHRs) contain a rapidly increasing volume of data which is, in general, distributed in autonomous heterogeneous databases. An emerging trend is the secondary use of such data (in most cases anonymized for privacy reasons), for purposes other than healthcare, such as for generating accurate disorder epidemiology datasets, real world treatment progress assessment and patient selection for clinical trials among others. The structure and purpose of the EHRs pose significant limitations in the richness and the complexity of the questions to be posed. In fact, the latter case introduces a greater challenge; it requires that two different domains (in terms of semantics) need to be interlinked - clinical research and healthcare. This paper aims at presenting a novel SPARQL query rewriting mechanism as part of an ontology-based approach for interlinking clinical research with healthcare EHRs for supporting automatic selection of patients who satisfy the eligibility criteria of clinical trials. Copyright 2012 ACM.	en
heal.journalName	ACM International Conference Proceeding Series	en
dc.identifier.doi	10.1145/2254129.2254189	en