Similarity Analyzer for Semantic Interoperability of Electronic Health Records Using Artificial Intelligence (AI)
DOI:
https://doi.org/10.23960/jesr.v1i2.13 - Abstract View: 450Keywords:
semantic interoperability; interoperability standards;electronic health records (EHR);artifical intelligence techniquesAbstract
The introduction of Electronic Health Records (EHR) has opened possibilities for solving interoperability issues within the healthcare sector. However, even with the introduction of EHRs, healthcare systems like hospitals and pharmacies remain isolated with no sharing of EHRs due to semantic interoperability issues. This paper extends our previous work in which we proposed a framework that dealt with semantic interoperability and security of EHR. The extension is the proposal of a cloud-based similarity analyzer for data structuring, data mapping, data modeling and conflict removal using Word2vec Artificial Intelligence (AI) technique. Different types of conflicts are removed from data in order to model data into common data types which can be interpreted by different stakeholders
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Copyright © JESR (Journal of Engineering and Scientific Research). This article is an open access article distributed under a CC-BY Creative Commons Attribution 4.0 International License, as presented on the link https://creativecommons.org/licenses/by/4.0/deed.