G Mohi-Ud-Din
Department of Computer Sciences, Faculty of Science, Liverpool John Moores University, Liverpool, United Kingdom

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Similarity Analyzer for Semantic Interoperability of Electronic Health Records Using Artificial Intelligence (AI) A Naveed; Y F Hu; T Sigwele; G Mohi-Ud-Din; Misfa Susanto
Journal of Engineering and Scientific Research Vol. 1 No. 2 (2019)
Publisher : Faculty of Engineering, Universitas Lampung Jl. Soemantri Brojonegoro No.1 Bandar Lampung, Indonesia 35141

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (418.041 KB) | DOI: 10.23960/jesr.v1i2.13

Abstract

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