Abstract FHIR.pdf 57,29KB
1000 Titel
  • FHIR RDF Data Transformation and Validation Framework and Clinical Knowledge Graphs: Towards Explainable AI in Healthcare
1000 Autor/in
  1. Prud'hommeaux, Eric |
  2. Solbrig, Harold |
  3. Xiao, Guohui |
1000 Erscheinungsjahr 2022
1000 Publikationstyp
  1. Kongressschrift |
1000 Online veröffentlicht
  • 2022-03-15
1000 Erschienen in
1000 Übergeordneter Kongress
1000 Lizenz
1000 Verlagsversion
  • |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • HL7 Fast Healthcare Interoperability Resources (FHIR) is rapidly becoming the standards framework for the exchange of electronic health record (EHR) data. By leveraging FHIRs resource-oriented architecture, FHIR RDF stands to become the first main-stream clinical data standard to incorporate the Semantic Web vision. The combination of FHIR, knowledge graphs and the Semantic Web enables a new paradigm to build classification and explainable artificial intelligence (AI) applications in healthcare. The objective of the tutorial is to introduce the FHIR RDF data transformation and validation framework, show how to build clinical knowledge graphs (cKG) in FHIR RDF, and provide the audience with hands-on opportunities on FHIR RDF and cKG tooling. Specifically:Topics regarding the FHIR RDF data transformation and validation framework include: 1. FHIR, and it´s representations FHIR JSON and FHIR RDF; 2. Conversion of FHIR JSON to FHIR RDF (via JSON-LD), use of the FHIR RDF playground, command line tools and HAPI-FHIR´s RDF (Turtle) support; 3. The Shape Expressions (ShEx) schemafor FHIR and its use for validating FHIR data; 4. FHIR structure definitions and their expression as JSON-LD contexts and ShEx schemas; In addition, the FHIR-Ontop-OMOP tool exposes the Observational Medical Outcomes Partnership (OMOP) data as a queryable Knowledge Graph compliant with the HL7 FHIR standard using the Ontop Virtual Knowledge Graph engine. In this tutorial, we demonstrate how to set up Ontop over a working connection to the OMOP PostgreSQL database using a mapping language. Thanks to the virtual approach, the FHIR RDF triples populated by declarative mapping do not need to be materialized. Instead, Ontop translates the SPARQL query over the FHIR RDF model to a SQL query over the OMOP database. We will illustrate the query translation process with some representative phenotype queries. Acknowledgements: This tutorial session is supported in part by the NIH FHIRCat R01 grant (R01 EB030529).
1000 Fächerklassifikation (DDC)
1000 DOI 10.4126/FRL01-006432244 |
1000 Liste der Beteiligten
1000 Label
1000 Förderer
  1. National Institutes of Health |
1000 Fördernummer
  1. R01 EB030529
1000 Förderprogramm
  1. FHIRCat
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer National Institutes of Health |
    1000 Förderprogramm FHIRCat
    1000 Fördernummer R01 EB030529
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6432244.rdf
1000 Erstellt am 2022-03-15T11:21:29.610+0100
1000 Erstellt von 320
1000 beschreibt frl:6432244
1000 Bearbeitet von 25
1000 Zuletzt bearbeitet Wed Apr 06 07:57:12 CEST 2022
1000 Objekt bearb. Wed Apr 06 07:56:39 CEST 2022
1000 Vgl. frl:6432244
1000 Oai Id
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1000 Sichtbarkeit Metadaten public
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