Augmented EHR: Enrichment of EHR with Contents from Semantic Web Sources
Source abstract
Abstract
This work presents methods to combine data from the Semantic Web into existing EHRs, leading to an augmented EHR. An existing EHR extract is augmented by combining it with additional information from external sources, typically linked data sources. The starting point is a standardized EHR extract described by an archetype. The method consists of combining specific data from the original EHR with contents from the external information source by building a semantic representation, which is used to query the external source. The results are converted into a standardized EHR extract according to an archetype. This work sets the foundations to transform Semantic Web contents into normalized EHR extracts. Finally, to exemplify the approach, the work includes a practical use case in which the summarized EHR is augmented with drug–drug interactions and disease-related treatment information.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Biomedical Text Mining and Ontologies · Semantic Web and Ontologies · Scientific Computing and Data Management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
ITACA Institute, Universitat Politècnica de València, 46022 Valencia, Spain
Veratech for Health SL, 46022 Valencia, Spain
Department of Computer Engineering and Science, Universitat Jaume I, 12071 Castellón, Spain
Funding
The Spanish Ministry of Economy and Competitiveness, the FEDER programme and the Spanish Ministry of Science, Innovation and Universities
References (42)
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