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Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach

Gerhard Kober, Livio Robaldo Orcid Logo, Adrian Paschke

Studies in Health Technology and Informatics, Volume: 293, Issue: d-Health 2022

Swansea University Author: Livio Robaldo Orcid Logo

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DOI (Published version): 10.3233/shti220348

Abstract

Decision-making based on so-called medical guidelines supported by semantic AI solutions is an essential and significant task for medical personnel in both a pre-clinical setting and an inner-clinical environment. Semantic representations of medical guidelines and Fast Healthcare Interoperability Re...

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Published in: Studies in Health Technology and Informatics
ISSN: 0926-9630 1879-8365
Published: IOS Press 2022
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URI: https://cronfa.swan.ac.uk/Record/cronfa59706
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first_indexed 2022-04-27T10:37:33Z
last_indexed 2023-01-11T14:41:10Z
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spelling 2022-10-12T12:03:31.8068631 v2 59706 2022-03-25 Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach b711cf9f3a7821ec52bd1e53b4f6cf9e 0000-0003-4713-8990 Livio Robaldo Livio Robaldo true false 2022-03-25 LAWD Decision-making based on so-called medical guidelines supported by semantic AI solutions is an essential and significant task for medical personnel in both a pre-clinical setting and an inner-clinical environment. Semantic representations of medical guidelines and Fast Healthcare Interoperability Resources (FHIR) using Semantic Web technologies, i.e., Resource Description Framework (RDF), rules (RuleML and Prova), and Shape Constraint Language (SHACL), provide a semantic knowledge base for the decision-making process and ease technical implementation and automation tasks. Current medical decision support systems lack Semantic Web integration using FHIR-RDF representations as a data source. In this paper, we implement a particular medical guideline using two different approaches: Prova [8] and SHACL [13]. We generate a series of raw FHIR-data for a selected guideline, the ABCDE approach, and compare the implemented two programs’ (Prova and SHACL) results. Both approaches deliver the same results in terms of content. Both may be used within a distributed medical environment depending on the need of organizations. Conference Paper/Proceeding/Abstract Studies in Health Technology and Informatics 293 d-Health 2022 IOS Press 0926-9630 1879-8365 16 5 2022 2022-05-16 10.3233/shti220348 http://dx.doi.org/10.3233/shti220348 COLLEGE NANME Law COLLEGE CODE LAWD Swansea University Other 2022-10-12T12:03:31.8068631 2022-03-25T14:46:15.0315480 Faculty of Humanities and Social Sciences Hilary Rodham Clinton School of Law Gerhard Kober 1 Livio Robaldo 0000-0003-4713-8990 2 Adrian Paschke 3 59706__24601__d1293f3f7c924b679d69f6a973ab9be2.pdf 59706.VOR with CC-BY-NC.pdf 2022-07-14T12:36:46.9254993 Output 229608 application/pdf Version of Record true Distributed under the terms of a Creative Commons Attribution Non Commercial (CC-BY-NC 4.0) Licence. true eng https://creativecommons.org/licenses/by-nc/4.0/
title Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
spellingShingle Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
Livio Robaldo
title_short Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
title_full Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
title_fullStr Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
title_full_unstemmed Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
title_sort Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
author_id_str_mv b711cf9f3a7821ec52bd1e53b4f6cf9e
author_id_fullname_str_mv b711cf9f3a7821ec52bd1e53b4f6cf9e_***_Livio Robaldo
author Livio Robaldo
author2 Gerhard Kober
Livio Robaldo
Adrian Paschke
format Conference Paper/Proceeding/Abstract
container_title Studies in Health Technology and Informatics
container_volume 293
container_issue d-Health 2022
publishDate 2022
institution Swansea University
issn 0926-9630
1879-8365
doi_str_mv 10.3233/shti220348
publisher IOS Press
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str Hilary Rodham Clinton School of Law{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}Hilary Rodham Clinton School of Law
url http://dx.doi.org/10.3233/shti220348
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description Decision-making based on so-called medical guidelines supported by semantic AI solutions is an essential and significant task for medical personnel in both a pre-clinical setting and an inner-clinical environment. Semantic representations of medical guidelines and Fast Healthcare Interoperability Resources (FHIR) using Semantic Web technologies, i.e., Resource Description Framework (RDF), rules (RuleML and Prova), and Shape Constraint Language (SHACL), provide a semantic knowledge base for the decision-making process and ease technical implementation and automation tasks. Current medical decision support systems lack Semantic Web integration using FHIR-RDF representations as a data source. In this paper, we implement a particular medical guideline using two different approaches: Prova [8] and SHACL [13]. We generate a series of raw FHIR-data for a selected guideline, the ABCDE approach, and compare the implemented two programs’ (Prova and SHACL) results. Both approaches deliver the same results in terms of content. Both may be used within a distributed medical environment depending on the need of organizations.
published_date 2022-05-16T04:17:13Z
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