The PrescIT Knowledge Graph: Supporting ePrescription to Prevent Adverse Drug Reactions-Reference-Cited by-同舟云学术

The PrescIT Knowledge Graph: Supporting ePrescription to Prevent Adverse Drug Reactions

Published:2023-05-18 Issue: Volume: Page:
ISSN:0926-9630
Container-title:Caring is Sharing – Exploiting the Value in Data for Health and Innovation
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Author:

Chytas Achilleas¹^ORCID,Dimitriadis Vlasios¹,Giannios Giorgos²,Grammatikopoulou Margarita²,Nikolaidis George³,Pliatsika Jenny³,Zachariadou Martha³,Karanikas Haralampos⁴,Kompatsiaris Ioannis²,Nikolopoulos Spiros²,Natsiavas Pantelis¹

Affiliation:

1. Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece

2. Information Technologies Institute, Centre for Research and Technology Hellas, Thessaloniki, Greece

3. Ergobyte SA, Thessaloniki, Greece

4. Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece

Abstract

Adverse Drug Reactions (ADRs) are an important public health issue as they can impose significant health and monetary burdens. This paper presents the engineering and use case of a Knowledge Graph, supporting the prevention of ADRs as part of a Clinical Decision Support System (CDSS) developed in the context of the PrescIT project. The presented PrescIT Knowledge Graph is built upon Semantic Web technologies namely the Resource Description Framework (RDF), and integrates widely relevant data sources and ontologies, i.e., DrugBank, SemMedDB, OpenPVSignal Knowledge Graph and DINTO, resulting in a lightweight and self-contained data source for evidence-based ADRs identification.

Publisher

IOS Press

Link

https://ebooks.iospress.nl/pdf/doi/10.3233/SHTI230203

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