TY - JOUR
T1 - Blending FHIR RDF and OWL
AU - Solbrig, Harold R.
AU - Prud’hommeaux, Eric
AU - Jiang, Guoqian
N1 - Funding Information:
This study is supported in part by NIH grants U01 HG009450 and U01 CA18094. This work was conducted using the Prot g resource, which is supported by grant GM10331601 from the National Institute of General Medical Sciences of the United States National Institutes of Health.
PY - 2017
Y1 - 2017
N2 - HL7 Fast Healthcare Interoperability Resources (FHIR) is rapidly becoming a major standard for the exchange of electronic healthcare information. FHIR defines a collection of “resources” to represent di erent information types and specifies how these resources are to be exchanged using XML, JSON and, as of the latest release, RDF. The FHIR specification also uses links to SNOMED CT and other ontologies as an integral component of the representation of clinical data. The combination of a standardized set of FHIR RDF tags with embedded ontology references o ers a number of interesting new possibilities for classification and categorization of clinical data, including recognizing prescriptions that contain particular drug categories, procedures that use a specific technique or approach, diagnoses of general disease categoreis (e.g. cancer, diabetes), etc. In this paper we investigate how FHIR RDF can be combined with ontologies in a description logic reasoner to achieve these goals.
AB - HL7 Fast Healthcare Interoperability Resources (FHIR) is rapidly becoming a major standard for the exchange of electronic healthcare information. FHIR defines a collection of “resources” to represent di erent information types and specifies how these resources are to be exchanged using XML, JSON and, as of the latest release, RDF. The FHIR specification also uses links to SNOMED CT and other ontologies as an integral component of the representation of clinical data. The combination of a standardized set of FHIR RDF tags with embedded ontology references o ers a number of interesting new possibilities for classification and categorization of clinical data, including recognizing prescriptions that contain particular drug categories, procedures that use a specific technique or approach, diagnoses of general disease categoreis (e.g. cancer, diabetes), etc. In this paper we investigate how FHIR RDF can be combined with ontologies in a description logic reasoner to achieve these goals.
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M3 - Conference article
AN - SCOPUS:85041475296
SN - 1613-0073
VL - 2042
JO - CEUR Workshop Proceedings
JF - CEUR Workshop Proceedings
T2 - 10th International Conference on Semantic Web Applications and Tools for Health Care and Life Sciences, SWAT4LS 2017
Y2 - 4 December 2017 through 7 December 2017
ER -