Conference Paper/Proceeding/Abstract 937 views 81 downloads
Modeling Medical Guidelines by Prova and SHACL Accessing FHIR/RDF. Use Case: The Medical ABCDE Approach
Studies in Health Technology and Informatics, Volume: 293, Issue: d-Health 2022
Swansea University Author: Livio Robaldo
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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...
Published in: | Studies in Health Technology and Informatics |
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ISSN: | 0926-9630 1879-8365 |
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IOS Press
2022
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URI: | https://cronfa.swan.ac.uk/Record/cronfa59706 |
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2023-01-11T14:41:10Z |
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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 HRCL 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 Hillary Rodham Clinton Law School COLLEGE CODE HRCL 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 |
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b711cf9f3a7821ec52bd1e53b4f6cf9e |
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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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Faculty of Humanities and Social Sciences |
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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 |
2022-05-16T20:23:00Z |
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11.047609 |