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Article

Big Data Analytics and Processing Platform in Czech Republic Healthcare

1
Solutia, s.r.o., 101 00 Prague, Czech Republic
2
School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology, Auckland 1010, New Zealand
3
Faculty of Electronic Engineering, Computer Science Department, University Niš, 18 000 Niš, Serbia
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(5), 1705; https://doi.org/10.3390/app10051705
Received: 1 February 2020 / Revised: 19 February 2020 / Accepted: 24 February 2020 / Published: 2 March 2020
(This article belongs to the Special Issue Big Data Analytics in Healthcare)
Big data analytics (BDA) in healthcare has made a positive difference in the integration of Artificial Intelligence (AI) in advancements of analytical capabilities, while lowering the costs of medical care. The aim of this study is to improve the existing healthcare eSystem by implementing a Big Data Analytics (BDA) platform and to meet the requirements of the Czech Republic National Health Service (Tender-Id. VZ0036628, No. Z2017-035520). In addition to providing analytical capabilities on Linux platforms supporting current and near-future AI with machine-learning and data-mining algorithms, there is the need for ethical considerations mandating new ways to preserve privacy, all of which are preconditioned by the growing body of regulations and expectations. The presented BDA platform, has met all requirements (N > 100), including the healthcare industry-standard Transaction Processing Performance Council (TPC-H) decision support benchmark in compliance with the European Union (EU) and the Czech Republic legislations. Currently, the presented Proof of Concept (PoC) that has been upgraded to a production environment has unified isolated parts of Czech Republic healthcare over the past seven months. The reported PoC BDA platform, artefacts, and concepts are transferrable to healthcare systems in other countries interested in developing or upgrading their own national healthcare infrastructure in a cost-effective, secure, scalable and high-performance manner. View Full-Text
Keywords: TPC-H; NoSQL database cluster; Vertica; real-time epidemic mapping; real-time pandemic tracking and integration; outbreak spread and risks data visualisation TPC-H; NoSQL database cluster; Vertica; real-time epidemic mapping; real-time pandemic tracking and integration; outbreak spread and risks data visualisation
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MDPI and ACS Style

Štufi, M.; Bačić, B.; Stoimenov, L. Big Data Analytics and Processing Platform in Czech Republic Healthcare. Appl. Sci. 2020, 10, 1705. https://doi.org/10.3390/app10051705

AMA Style

Štufi M, Bačić B, Stoimenov L. Big Data Analytics and Processing Platform in Czech Republic Healthcare. Applied Sciences. 2020; 10(5):1705. https://doi.org/10.3390/app10051705

Chicago/Turabian Style

Štufi, Martin, Boris Bačić, and Leonid Stoimenov. 2020. "Big Data Analytics and Processing Platform in Czech Republic Healthcare" Applied Sciences 10, no. 5: 1705. https://doi.org/10.3390/app10051705

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