A Semantic Web based Framework for Linking Healthcare Information with Computational Physiology Models

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dc.contributor.author Atalag, Koray en
dc.contributor.author Kalbasi, R en
dc.contributor.author Nickerson, David en
dc.coverage.spatial Rotorua, New Zealand en
dc.date.accessioned 2018-10-08T20:39:17Z en
dc.date.issued 2017-11-02 en
dc.identifier.uri http://hdl.handle.net/2292/39531 en
dc.description.abstract Linking healthcare information which nowadays is becoming vastly available with computational physiology models can be instrumental for enabling personalised and predictive clinical decision support systems. In the computational physiology domain semantic interoperability heavily relies on Semantic Web technologies and utilise ontology-based annotations but a wealth of useful information and knowledge sits in EHRs where this technology has limited use. openEHR and ISO13606 provide open standards for the structure, storage and exchange of healthcare data which readily support terminology/ontology based bindings that be exploited to link the two domains. This linkage will be bidirectional which means it will enable data discovery for computational modellers and also model discovery for clinical users. Since the openEHR specifications now underpin many national programs and regional implementations this can unlock unsurmountable potential to create both model and data driven personalised and predictive analytics. Having fit for purpose and standardised ontologies (such as Gene Ontology, Foundational Model of Anatomy) and clinical terminology (such as SNOMED CT, LOINC, ICD) have been a critical first step. However there is still a need to create mappings between these ontologies and develop standard annotation protocols. We describe our high-level methodology with an emphasis on ontology mapping using a crowd-sourcing approach. en
dc.relation.ispartof 16th Annual Health Informatics New Zealand (HINZ2017) Conference 2017 en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title A Semantic Web based Framework for Linking Healthcare Information with Computational Physiology Models en
dc.type Conference Item en
dc.rights.holder Copyright: The author en
pubs.author-url http://www.hinz.org.nz/?page=2017HINZConf en
pubs.finish-date 2017-11-03 en
pubs.start-date 2017-11-01 en
dc.rights.accessrights http://purl.org/eprint/accessRights/RestrictedAccess en
pubs.subtype Proceedings en
pubs.elements-id 674208 en
pubs.org-id Bioengineering Institute en
pubs.org-id ABI Associates en
pubs.record-created-at-source-date 2017-09-25 en

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